BLND

Lenders using Blend Autopilot’s pre-underwriting agent saw 10-15% higher pull-through rates and an estimated $600 lower cost per funded loan SAN FRANCISCO, August 20, 2026--(BUSINESS WIRE)--Blend (NYSE: BLND) today shared early production results for Autopilot, its agentic system for lending, showing a marked increase in pull-through rates and a reduction in loan-cycle times. Since March 2026, Autopilot's pre-underwriting agent has processed more than 50,000 live production loans across lenders on Blend's Home Lending platform. Across the analyzed cohorts, lenders using Autopilot’s pre-underwriting agent saw: Pull-through rates 10% to 15% higher Loan-cycle times shortened by 2 to 4 days 4.5 hours of loan fulfillment tasks automated on average per loan An estimated $600 saved in fulfillment costs per funded loan The early impact comes from live production loans with real borrowers, not pilots or simulations. Blend compared 24 lender and loan-type cohorts against their own pre-Autopilot performance, covering more than 175,000 loans. The results point to a shift larger than efficiency gains. Most AI in lending today accelerates individual steps in a process that still runs sequentially, with each stage waiting on the one before it. Autopilot's agent-first model works the file in parallel and in real time, which changes what the origination process costs, how long it takes, and when borrowers get answers. "I think the biggest mistake people make with AI is trying to be too incremental. Our approach is to ask: What would this industry look like if you designed it from the ground up around agents?" said Nima Ghamsari, Co-founder and Head of Blend. "That's no longer a thought experiment. Autopilot has run on more than 50,000 live production loans, and the economics are already changing." How Autopilot Works More than half of borrowers apply for a mortgage loan outside business hours, and more than 90% of borrowers who submit do so within 24 hours of starting, according to Blend network data. Borrower intent is highest in that first day and fades quickly: friction that stalls an application overnight doesn't just delay it, it risks losing the borrower to a competitor. For lenders, that makes the first 24 hours a critical window to keep borrowers moving, even when no one is staffed to respond. Autopilot operates inside that window. It reviews the application in real time, identifies missing or inconsistent information, completes pre-underwriting work, and follows up with the borrower while they are still engaged. Files reach processing and underwriting cleaner, reducing rework, borrower callbacks, and late-stage conditions. "Instead of a person taking the first pass and an agent checking the work, Autopilot agents are working behind the scenes before a human ever touches the file. Rules-based automation could never do that, because rules only work on predictable files, and underwriters spend all their time on the ones that aren't," Ghamsari added. "By the time it reaches a loan team, the work is done, which gives them their time back to spend with borrowers instead of paperwork." Availability Autopilot became commercially available on July 1 for lenders on Blend’s Home Lending platform. Six lenders have already signed contracts that include Autopilot. For more information, visit blend.com/platform/blend-autopilot/. About Blend Blend Labs Inc. (NYSE: BLND) is a leading origination platform for digital banking solutions. Financial providers, from large banks, fintechs, and credit unions to community and independent mortgage banks, use Blend’s platform to transform banking experiences for their customers. Learn more at blend.com. View source version on businesswire.com: https://www.businesswire.com/news/home/20260820158280/en/ Contacts Press contact [email protected]

Interested in Blend Labs, Inc.? Here are five stocks we like better. Blend delivered a profitable second quarter: Revenue rose 7% year over year to $33.8 million, while non-GAAP operating income reached $7 million, above guidance. The company ended the quarter with $44.9 million in cash and no debt. Autopilot showed early traction: More than 65 lenders activated the AI platform during its preview, with nearly 50,000 loans processed and reported improvements in pull-through rates, cycle times and fulfillment productivity. Six lenders had signed contracts as of the earnings call. Near-term growth remains pressured: Higher mortgage rates, weak refinancing activity and customer churn notices led to conservative third-quarter guidance, including projected revenue of $31.5 million to $33.5 million and funded loan volume of 200,000 to 210,000. Management cautioned that Autopilot revenue may take time to scale. Blend Labs (NYSE:BLND) reported second-quarter revenue near the high end of its guidance range and non-GAAP operating income above its outlook, while management pointed to continued mortgage-market pressure and early commercialization progress for its Autopilot artificial intelligence product. Total revenue was $33.8 million, up 7% from a year earlier. Non-GAAP operating income reached $7 million, exceeding the company’s guided range of $5.5 million to $6.5 million. Blend ended the quarter with $44.9 million in cash, cash equivalents and marketable securities and no debt. → Meta’s Earnings Drop Shows Wall Street Wants More Than Ad Growth “The second quarter was another disciplined, profitable quarter for Blend,” Co-founder and Head of Blend Nima Ghamsari said during the company’s earnings call. Mortgage Suite revenue rose 7% year over year to $19.2 million. Funded mortgage loans on Blend’s platform increased 14% to approximately 233,000 during the quarter. Economic value per funded loan was $79, compared with $83 in the first quarter. Head of Finance and Administration Jason Ream said the decline was primarily mathematical, as higher second-quarter loan volumes lower the per-loan calculation when fixed-fee customer arrangements are included. → 4 Oil and Gas ETF Plays as Prices Stay Sky-High Consumer Banking Suite revenue increased 6% from a year earlier to $12.2 million, while Professional Services revenue was $2.4 million. Non-GAAP gross profit totaled $26.5 million, producing a non-GAAP gross margin of 78.3%, compared with 76.1% a year earlier. Ream said the result was in line with the company’s normalized 77% to 78% gross-margin framework, despite growing, though still relatively low, model costs associated with Autopilot. → Sandisk Just Delivered a Blowout Quarter—Here's Why the Stock Is Falling Non-GAAP operating expenses were approximately flat year over year at $19.5 million. Free cash flow was $6.9 million in the quarter. Blend also repurchased 11 million shares at an average price of $1.65 per share during the quarter. Year to date, the company has repurchased 22.2 million shares for $36.8 million, leaving about $13.2 million available under its $50 million authorization. Autopilot, Blend’s AI-driven agent platform for lenders, became commercially available July 1. Ghamsari said more than 65 lenders activated the product during a four-month preview period beginning in February, during which cumulative loans processed through Autopilot exceeded 45,000. He later said the number was approaching 50,000 loans. Based on preliminary data from loans processed through the system, Ghamsari said customers have seen a 10% to 15% improvement in pull-through rates, cycle-time improvements of two to four days and an average of about 4.5 hours of loan-fulfillment work automated per loan. Six lenders had signed contracts that include Autopilot as of the call, including mortgage servicer Onity. Blend is initially selling the service through flat-fee, one-year agreements that provide full access. Over time, the company intends to shift paid tiers toward a per-funded-loan model, aligning its revenue with customer outcomes rather than the number of tasks performed. Ghamsari said Blend believes its position at the borrower’s point of contact, its historical loan-processing data, its infrastructure and compliance framework, and its lender relationships distinguish the offering from generic AI tools. He said Autopilot can hand loan files back to lender teams when it is uncertain, while people remain in control of key decisions. The company has not yet launched Autopilot for Consumer Banking Suite customers, although Ghamsari said the platform has baseline capabilities to support those customers and Blend is engaged with early customers on potential expansion. He described the company’s approach as working deeply with a limited number of “lighthouse customers” before broadening availability. Blend is also applying AI internally under what management calls “Blend 3.0,” an agentic-first operating model. Ghamsari said the company’s engineering team increased throughput, as measured by pull requests, by 3.6 times since January with roughly the same headcount. AI agents are also being used to review incoming support tickets, draft responses and configuration changes, assist with customer-call follow-ups, and perform first-pass work in parts of the finance close process. Management said the company signed 14 new deals and expansions during the quarter. Those included a new large credit-union customer that selected both Blend and Autopilot at the outset, as well as a cross-sale of Rapid Refi and Rapid Home Equity products to a top-five credit union. Ghamsari said Blend’s overall pipeline continued to grow, while its late-stage pipeline—deals the company targets for closing within the next quarter—grew nearly 40% between March and June. The pipeline includes a large mortgage customer, a top-20 financial institution, and Rapid and Autopilot opportunities. Management expects two additional large Rapid deals to close in the coming months, though it noted that large institutions may require time for governance reviews of agentic tools. Management said mortgage rates had risen from about 6.4% in May to roughly 6.8% in recent weeks, keeping refinance and purchase activity muted. Ream said Blend’s outlook is more conservative than Fannie Mae’s latest mortgage-volume forecast because the company expects refinance volumes to remain weak in a higher-for-longer interest-rate environment. Blend also saw an increase in churn notices during the quarter. Ream said the affected customers generally planned to move to existing lower-cost or free point solutions, rather than AI-native offerings or in-house tools. The company expects the impact to be manageable, at a low-single-digit percentage of annual revenue. Third-quarter revenue is expected to be $31.5 million to $33.5 million, representing a year-over-year change of negative 4% to positive 2%. Third-quarter funded loan volume is projected at approximately 200,000 to 210,000 loans. Third-quarter non-GAAP operating income is expected to be $3.5 million to $4.5 million. Fourth-quarter funded loan volume is expected to be approximately 180,000 to 190,000 loans, down about 10% to 15% year over year. Ream said investors should remain cautious about incorporating Autopilot revenue into models until more customers progress through the sales and deployment funnel. Management said it sees customer wins, product development velocity and Autopilot commercialization as factors that could support growth acceleration heading into 2027. Blend Labs, Inc operates as a financial technology company that offers a digital consumer banking platform designed to simplify and automate the lending and account opening processes for banks and credit unions. Its cloud-native software enables financial institutions to deliver a more seamless customer experience by consolidating multiple steps—such as application intake, identity verification, document collection and underwriting—into a unified digital workflow. Blend's platform is built to integrate with existing core banking systems and third-party data providers, allowing clients to accelerate loan origination and deposit account opening while maintaining compliance and security standards. The company's product suite includes solutions for mortgage origination, home equity lending, consumer personal lending and deposit account opening. This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest reporting and unbiased coverage. Please send any questions or comments about this story to [email protected]. The article "Blend Labs Q2 Earnings Call Highlights" was originally published by MarketBeat. View MarketBeat's top stocks for August 2026.

This article first appeared on GuruFocus. Total Revenue: $33.8 million, up 7% year-over-year, near the high end of guidance. Mortgage Suite Revenue: $19.2 million, up 7% year-over-year. Consumer Banking Suite Revenue: $12.2 million, up 6% year-over-year. Professional Services Revenue: $2.4 million, consistent with expectations. Funded Mortgage Loans: Approximately 233,000 in Q2, up 14% year-over-year. Economic Value per Funded Loan: $79, consistent with guidance. Non-GAAP Gross Profit: $26.5 million. Non-GAAP Gross Margin: 78.3%, up from 76.1% in Q2 2025. Non-GAAP Operating Expenses: $19.5 million, roughly flat year-over-year. Non-GAAP Operating Income: $7 million, above the high end of guidance, with a margin of 20.6%. Free Cash Flow: $6.9 million for the quarter. Cash and Marketable Securities: $44.9 million at quarter end, with zero debt. Share Repurchases: 11 million shares repurchased at an average price of $1.65 per share in Q2; 22.2 million shares year-to-date for $36.8 million. Warning! GuruFocus has detected 2 Warning Signs with BLND. Is BLND fairly valued? Test your thesis with our free DCF calculator. Release Date: August 06, 2026 For the complete transcript of the earnings call, please refer to the full earnings call transcript. Blend Labs Inc (NYSE:BLND) delivered a solid second quarter with total revenue of $33.8 million, up 7% year-over-year and near the high end of its guidance range. Autopilot, the company's AI agent product, became commercially available on July 1st, with over 65 lenders activating it and 6 contracts already signed, including a major mortgage servicer. Early Autopilot data shows significant customer benefits, including a 10-15% improvement in pull-through rates, a 2-4 day reduction in cycle time, and automation of 4.5 hours of loan fulfillment tasks per loan. The company's internal AI transformation (Blend 3.0) has led to a 3.6x increase in engineering throughput with roughly the same headcount, positioning it for faster product innovation and cost efficiencies. Blend Labs Inc (NYSE:BLND) reported strong profitability with non-GAAP operating income of $7 million, above the high end of guidance, and a non-GAAP operating margin of 20.6%, an improvement of nearly 6 points year-over-year. The company's late-stage pipeline grew nearly 40% between March and June, indicating strong future growth potential despite current macro headwinds. Blend Labs Inc (NYSE:BLND) continues to return capital to shareholders, repurchasing 22.2 million shares year-to-date for $36.8 million, with zero debt and a strong cash position of $44.9 million. The macro environment remains a significant headwind, with mortgage rates rising from 6.4% to 6.8%, which is expected to mute refinance and purchase activity in the market. The company's Q3 revenue guidance of $31.5 million to $33.5 million implies potential negative year-over-year growth of up to 4%, reflecting a cautious outlook. Blend Labs Inc (NYSE:BLND) saw an uptick in churn notices this quarter, with customers planning to move to lower-cost or free point solutions, which could impact annual revenue in the low single digits. The company's Q4 funded loan volume is expected to decline 10-15% year-over-year, reflecting a conservative view on market volumes and the roll-off of a large customer. Autopilot revenue is not yet expected to significantly impact financials, and the company cautions against incorporating it into models, as large financial institutions take time to navigate governance around agentic tools. Economic value per funded loan declined to $79 in Q2 from $83 in Q1, partially offsetting volume growth and reflecting the impact of fixed-fee arrangements. The company's Q3 non-GAAP operating margin is expected to decline to approximately 12% from 20.6% in Q2, partly due to a $1.5 million sequential step-up in sales and marketing expenses for its annual customer event. Q: Nima, last quarter you commented that you thought agents and Autopilot provided a path to potentially see 10% to 15% incremental revenue growth in '27. Given you're now a month into selling the 1-year flat-rate Autopilot contracts, you get 6 lenders signed and the commentary on it takes a little while to get through governance at large financial institutions, does that sentiment hold today?A: Nima Ghamsari (Co-founder and Head of Blend): I don't want to give any additional further guidance there, but the pipeline is good in terms of what we signed, and a large number of our largest financial institutions are leaning in. The early numbers from Autopilot are encouraging, with about 50,000 loans processed in the last few months. We're seeing a dual tailwind of our own work accelerating and the underlying models getting better, which positions us as a compounding machine. It's early, but the signs are more encouraging than I would have thought in January. Q: For Blend 3.0, how do you think about the balance between faster innovation and better products versus OpEx leverage? Based on today's update, when does the 3.6 times increase in pull requests turn into either revenue or operating leverage?A: Nima Ghamsari (Co-founder and Head of Blend): Some of the revenue side is answered by the previous answerthese products take time to become a reality in a regulated market, which is part of our moat. We're focused on the medium term, specifically 2027, as these deals mature and get live at scale. The beauty of being a profitable company in a terrible mortgage market is that we can focus on medium and long-term results rather than driving immediate results at the expense of 2027 and 2028. Q: I just want to double click on Jason's comment on the uptick on churn notices in the quarter. I understand that the impact is pretty small, but could you share a bit more color here? Are these going to be like the AI-native point solutions that have just gone on the market, or maybe customers are moving to build in-house?A: Jason Ream (Head of Finance and Administration): We saw people going to existing low-cost providers. It's hard to call it a trend with limited data points, but our customers are suffering with the rate environment and macro, and they're looking for ways to save money. That's what we're seeing in the few cases we've had. Q: One of the broader trends across the mortgage market has been market share shifting towards the broker channel. How do you think this could affect Blend and where do you think trends are going?A: Nima Ghamsari (Co-founder and Head of Blend): We've noticed this trend over the past few years, with the broker channel growing from single-digit percentages to high teens. However, our customers are the ones betting on the future and investing in new technologies. This year especially, we're seeing customers say it's time to invest in the future. Our customer base is focused on improvement and will continue to win in this market. Q: On Autopilot, encouraging early interest, but wondering how you're thinking about your opportunity to orchestrate the entire funnel of the workflow and all of those individual points compounding on each other as it pertains to customer ROI, maybe how that's driving conviction in the Autopilot strategy and what's really differentiated from some of those potentially alternative tools?A: Nima Ghamsari (Co-founder and Head of Blend): Typical solutions in the market take an existing process and layer on something new, which is the antithesis of Autopilot. Our vision is for Rapid to get you a real-time offer and Autopilot to get you from that offer to clear to close in the first session. The beauty of Autopilot being an open harness is it doesn't care what systems are in place. We're driving towards loans being ready to close at 2:00 a.m., with the system checking documents and working with the consumer in real time. That's where the compounding benefit will come into play. Q: If we look at EVPFL, that's troughed in 2Q, expected to kind of step up. I guess just clarity around how much of that is the mechanics of lower volume uplift versus maybe incremental product cross-sell. And I know we're not saying Autopilot is layering in any capacity, but if at all any extent that that's driving some of that uplift as well.A: Jason Ream (Head of Finance and Administration): Our volume expectations aren't that much different for Q2 and Q3, so I think it's mostly just the dynamics in the business. We're not guiding to a very different number, so I would think about Q2 and Q3 as sort of steady state with each other. Q: It's great to see the impact Autopilot is having on the mortgage side. I'm just wondering, is Autopilot also available to your Consumer Banking clients and maybe you can speak to the opportunity there?A: Nima Ghamsari (Co-founder and Head of Blend): It's built into our platform, so we have the baselines in place to support all of our customers. It's a big request we get from customers who have multiple product lines with us. We don't have that live yet, but stay tuned. Our approach is to pick a few lighthouse customers, drive it deep with them, prove the value, and then expand to the market within a quarter or two. Q: You mentioned 2 deals in the credit union channel. Maybe we can get an update on the channel in general and what the pipeline there looks like?A: Nima Ghamsari (Co-founder and Head of Blend): We don't have a specific breakout of credit union versus bank versus independent mortgage company, but we have a great base of customers from the largest credit unions down to medium and community credit unions. They are very member self-serve first, which aligns with our product principles of helping someone applying at 2 in the morning get a full approval. The Rapid Suite and Autopilot fit really well with this segment. For the complete transcript of the earnings call, please refer to the full earnings call transcript.

SAN FRANCISCO, August 06, 2026--(BUSINESS WIRE)--Blend Labs, Inc. (NYSE: BLND), a leading origination platform for digital banking solutions, today announced its second quarter 2026 financial results. "We delivered Q2 with revenue near the high end and non-GAAP operating income above the high end of our guidance, and we did it in a market that isn't giving us much help," said Nima Ghamsari, Co-founder and Head of Blend. "The bigger milestone is that Autopilot became commercially available on July 1, and we’ve already got six lenders signed on. Paired with the agent-first transformation happening inside Blend, we're working toward re-accelerating growth in 2027." Second Quarter Highlights Solid Results: Total revenue near the high end of guidance and non-GAAP operating income above the high end of guidance. New Deals and Expansions: Added or expanded 14 customer relationships in the second quarter — including 6 deals with Autopilot. Returning Capital to Shareholders: Repurchased 11.0 million shares in the second quarter for $18.2 million — $13.2 million remaining on the existing authorization at quarter end. Second quarter revenue was $33.8 million, an increase of 7% compared to the second quarter of 2025. Software platform revenue was $31.4 million, up 7% year-over-year, and Professional services revenue was $2.4 million compared to $2.2 million in the second quarter of 2025. Total GAAP gross profit margin was 74%, compared to 74% in the second quarter of 2025, and non-GAAP gross profit margin was 78%, up from 76% in the same period last year. GAAP operating loss was $1.6 million, compared to a loss of $4.8 million in the second quarter of 2025. Non-GAAP operating income was $7.0 million, up from $4.6 million in the same period last year. GAAP diluted net loss from continuing operations attributable to common stockholders per share was $0.03 in both the second quarter of 2026 and the same period last year. Non-GAAP diluted net income from continuing operations attributable to common stockholders per share was $0.00 in the second quarter of 2026 and in the second quarter of 2025. Third Quarter Outlook Blend is providing guidance for the third quarter of 2026 as follows: We have not provided the forward-looking GAAP equivalent to our non-GAAP Operating Income outlook, or a GAAP reconciliation as a result of the uncertainty regarding, and the potential variability of, stock-based compensation, which is affected by our hiring and retention needs and future prices of our stock, and non-recurring, infrequent or unusual items. Webcast Information On Thursday, August 6 at 4:30 pm ET, Blend will host a live discussion of its second quarter 2026 financial results. A link to the live discussion will be made available on the Company’s investor relations website at https://investor.blend.com. A replay will also be made available following the discussion at the same website. Forward-Looking Statements This press release contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. These statements may relate to, but are not limited to, quotations of management; the "Third Quarter Outlook" section above; Blend’s expectations regarding its financial condition and operating performance, including growth expectations and opportunities, investments and plans for future operations and competitive position; Blend’s partnerships and expectations related to such partnerships on Blend’s products and business; Blend’s products, sales pipeline, and technologies; Blend’s customers and customer relationships, including the businesses of such customers and their positions in the market; Blend’s ability to achieve or maintain profitability in the future; projections for mortgage loan origination volumes, including projections provided by third parties; and other macroeconomic and industry conditions. Forward-looking statements are inherently subject to risks and uncertainties, some of which cannot be predicted or quantified. In some cases, you can identify forward-looking statements by terminology such as "may," "will," "should," "expect," "plan," "anticipate," "could," "would," "intend," "target," "project," "contemplate," "believe," "estimate," "predict," "potential" or "continue" or the negative of these terms or other comparable terminology that concern Blend’s expectations, strategy, plans or intentions. You should not put undue reliance on any forward-looking statements. Forward-looking statements should not be read as a guarantee of future performance or results and will not necessarily be accurate indications of the times at, or by which such performance or results will be achieved, if at all. Forward-looking statements are based on information available at the time those statements are made and/or management’s good faith beliefs and assumptions as of that time with respect to future events and are subject to risks and uncertainties that could cause actual performance or results to differ materially from those expressed in or suggested by the forward-looking statements. These risks and uncertainties include the risks that: ongoing uncertainty or deterioration in economic conditions, such as increased mortgage interest rates, credit availability, real estate prices, tariffs and regulatory changes, inflation or consumer confidence, adversely affect our industry, markets and business; we fail to retain our existing customers or to acquire new customers in a cost-effective manner; our customers fail to maintain their utilization of our products and services; our relationships with any of our key customers were to be terminated or the level of business with them significantly reduced over time; we are unable to compete in highly competitive markets; we are unable to manage our growth; we are unable to make accurate predictions about our future performance due to our limited operating history in an evolving industry and evolving markets; our restructuring actions do not result in the desired outcomes or adversely affect our business, impairment charges on certain assets have an adverse effect on our financial condition and results of operations; changes to our expectations regarding our share repurchase program; our strategic initiatives, including our decision to exit our Title business, could adversely affect our financial condition; or we are unable to generate sufficient cash flows or otherwise maintain sufficient liquidity to fund our operations and satisfy our liabilities. Further information on these risks and other factors that could affect our financial results are set forth in our filings with the Securities and Exchange Commission, including in our Annual Report on Form 10-K for the year ended December 31, 2025, our Quarterly Report on Form 10-Q for the quarter ended March 31, 2026 and will be set forth in our Quarterly Report on Form 10-Q for the quarter ended June 30, 2026. In light of these risks and uncertainties, the forward-looking events and circumstances discussed in this press release may not occur and actual results could differ materially from those anticipated or implied in the forward-looking statements. These factors could cause actual results, performance, or achievement to differ materially and adversely from those anticipated or implied in the forward-looking statements. Moreover, we operate in a very competitive and rapidly changing environment. New risks and uncertainties emerge from time to time, and it is not possible for us to predict all risks and uncertainties that could have an impact on the forward-looking statements contained in this press release. Except as required by law, Blend does not undertake any obligation to publicly update or revise any forward-looking statement, whether as a result of new information, future developments, or otherwise. About Non-GAAP Financial Measures and Other Performance Metrics In addition to financial measures prepared in accordance with GAAP, this press release and the accompanying tables contain, and the conference call will contain, non-GAAP financial measures, including non-GAAP gross profit and non-GAAP gross margin, non-GAAP operating expenses, non-GAAP income (loss) from operations, non-GAAP operating margin, non-GAAP net income (loss) from continuing operations, and non-GAAP diluted net income (loss) per share from continuing operations attributable to common stockholders. Our management uses these non-GAAP financial measures internally in analyzing our financial results and believes they are useful to investors, as a supplement to the corresponding GAAP financial measures, in evaluating our ongoing operational performance and trends, in allowing for greater transparency with respect to measures used by our management in their financial and operational decision making, and in comparing our results of operations with other companies in the same industry, many of which present similar non-GAAP financial measures to help investors understand the operational performance of their businesses. We adjust the following items from our non-GAAP financial measures as detailed in the reconciliations below: Stock-based compensation. We exclude stock-based compensation, which is a non-cash expense, from our non-GAAP financial measures because we believe that excluding this cost provides meaningful supplemental information regarding operational performance. In particular, companies calculate stock-based compensation expense using a variety of valuation methodologies and subjective assumptions, and expense related to stock-based awards can vary significantly based on the timing, size and nature of awards granted. Workforce reduction costs. We exclude restructuring costs related to workforce reductions as these costs primarily include employee severance and other costs directly associated with resource realignments incurred in connection with changing strategies or business conditions. These costs can vary significantly in amount and frequency based on the nature of the actions as well as the changing needs of our business and we believe that excluding them provides easier comparability of pre- and post-restructuring operating results. Abandoned and terminated facilities costs. We exclude costs related to abandoned and terminated leases as these costs related to a one-time strategic business decision, are non-recurring or short-term in nature and are not reflective of our ongoing operations. Thus we believe that excluding these charges for purposes of calculating the non-GAAP financial measures provides more meaningful period to period comparisons. Litigation contingencies and related professional services costs. We exclude costs related to litigation contingencies, which represent reserves for legal settlements, as well as the related professional service fees incurred related to these matters. These costs are non-recurring in nature and we do not believe they have a direct correlation to the operation of our business. Transaction-related costs. We exclude costs related to strategic transactions from our non-GAAP financial measures as we do not consider these costs to be related to organic continuing operations of our business or relevant to assessing the long-term performance of the impact of such transactions. These adjustments allow for more accurate comparisons of the financial results to historical operations and forward looking guidance. These non-recurring costs include financial advisory, legal, and other transactional costs incurred in connection with investing or divesting activities. Impairment of capitalized internal-use software. We exclude the impairment of capitalized internal-use software because we do not believe this non-cash expense has a direct correlation to the operation of our business and is non-recurring in nature. Amortization of capitalized internal-use software. We exclude the amortization of capitalized internal-use software because we do not believe this non-cash expense has a direct correlation to the operation of our business. Foreign currency gains and losses. We exclude unrealized gains and losses resulting from remeasurement of assets and liabilities from foreign currency into the functional currency as we do not believe these gains and losses to be indicative of our business performance and excluding these gains and losses provides information consistent with how we evaluate our operating results. Equity in losses of equity method investees, net of tax. We exclude our share of earnings of our equity method investee as we do not believe these earnings to be indicative of our business performance and excluding these earnings provides information consistent with how we evaluate our operating results. Economic Value per Funded Loan. In our Mortgage Suite, Economic Value per Funded Loan represents the contractual rates for mortgage and mortgage-related products multiplied by the number of loans funded or transactions completed, as applicable, by a customer in the specified period (economic value), divided by the total number of loans funded by all Mortgage Suite customers in that same period. Economic value per funded loan is segregated into three categories: 1) core software, 2) add-on products and 3) partnerships. Core software consists of economic value generated through Mortgage and Blend Close. Add-on products consists of economic value historically generated through Blend Income Verification and Blend Insurance Agency, which have transitioned to partnership models; following the transition, economic value from these products is reported under Partnerships. Partnerships consists of economic value generated from partners through our integrated marketplace. The value derived from products associated with the mortgage application stage is aligned with the timing of funding the related loan (typically a 1-3 month delay from the time of application). Additionally, the value that is associated with fixed platform fees is recognized as revenue ratably over the contractual period, which naturally creates peaks and troughs that align with quarters of low and high mortgage loans funded. We use Economic Value per Funded Loan to measure our success at broadening the client relationships from the underlying mortgage transactions and selling additional products through our software platform. Our non-GAAP financial measures also include non-GAAP operating margin, which is defined as non-GAAP income (loss) from operations divided by total revenue. We believe that the presentation of non-GAAP operating margin provides useful information to investors as it is one of the metrics we use to assess our operating and financial performance, and also may be a useful metric for investors to compare our operating and financial results with other companies in our industry. In addition, our non-GAAP financial measures include the following measures related to our liquidity: free cash flow, unlevered free cash flow and free cash flow margin. Free cash flow is defined as net cash flow from operating activities less cash spent on additions to property, equipment, internal-use software and intangible assets. Unlevered free cash flow is defined as free cash flow before cash paid for interest on our outstanding debt. Free cash flow margin is defined as free cash flow divided by total revenue. We believe information regarding free cash flow and free cash flow margin provides useful information to investors as a basis for comparing our performance with other companies in our industry and as a measurement of the cash generation that is available to invest in our business and meet our financing needs. We present unlevered free cash flow primarily for historical comparisons. In April 2024, we repaid in full all amounts outstanding and payable under our debt obligations and therefore eliminated any debt service obligations. We have not separately adjusted for certain tax-related impacts of our non-GAAP financial measures, as they are not material to our overall non-GAAP results for the periods presented. It is important to note that the particular items we exclude from, or include in, our non-GAAP financial measures may differ from the items excluded from, or included in, similar non-GAAP financial measures used by other companies in the same industry. In addition, other companies may utilize metrics that are not similar to ours. The non-GAAP financial information is presented for supplemental informational purposes only and is not intended to be considered in isolation or as a substitute for, or superior to, financial information prepared and presented in accordance with GAAP. There are material limitations associated with the use of non-GAAP financial measures since they exclude significant expenses and income that are required by GAAP to be recorded in our financial statements. Please see the reconciliation tables at the end of this release for the reconciliation of GAAP and non-GAAP results. Management encourages investors and others to review Blend’s financial information in its entirety and not rely on a single financial measure. About Blend Blend Labs, Inc., (NYSE: BLND) is a leading origination platform for digital banking solutions. Financial providers—from large banks, fintechs, and credit unions to community and independent mortgage banks—use Blend’s platform to transform banking experiences for their customers. Better banking starts on Blend. To learn more, visit blend.com. View source version on businesswire.com: https://www.businesswire.com/news/home/20260806201407/en/ Contacts Investor [email protected] [email protected]

Blend Labs (BLND) reported break-even quarterly earnings per share versus the Zacks Consensus Estimate of $0.02. This compares to break-even earnings per share a year ago. These figures are adjusted for non-recurring items. This quarterly report represents an earnings surprise of -100.00%. A quarter ago, it was expected that this cloud-based platform for financial companies would post earnings of $0.02 per share when it actually produced break-even earnings, delivering a surprise of -100%. Over the last four quarters, the company has not been able to surpass consensus EPS estimates. Blend Labs, which belongs to the Zacks Internet - Software industry, posted revenues of $33.84 million for the quarter ended June 2026, surpassing the Zacks Consensus Estimate by 2.54%. This compares to year-ago revenues of $31.52 million. The company has topped consensus revenue estimates four times over the last four quarters. The sustainability of the stock's immediate price movement based on the recently-released numbers and future earnings expectations will mostly depend on management's commentary on the earnings call. Blend Labs shares have lost about 33.9% since the beginning of the year versus the S&P 500's gain of 12.8%. While Blend Labs has underperformed the market so far this year, the question that comes to investors' minds is: what's next for the stock? There are no easy answers to this key question, but one reliable measure that can help investors address this is the company's earnings outlook. Not only does this include current consensus earnings expectations for the coming quarter(s), but also how these expectations have changed lately. Empirical research shows a strong correlation between near-term stock movements and trends in earnings estimate revisions. Investors can track such revisions by themselves or rely on a tried-and-tested rating tool like the Zacks Rank, which has an impressive track record of harnessing the power of earnings estimate revisions. Ahead of this earnings release, the estimate revisions trend for Blend Labs was unfavorable. While the magnitude and direction of estimate revisions could change following the company's just-released earnings report, the current status translates into a Zacks Rank #4 (Sell) for the stock. So, the shares are expected to underperform the market in the near future. You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here. It will be interesting to see how estimates for the coming quarters and the current fiscal year change in the days ahead. The current consensus EPS estimate is $0.01 on $33.9 million in revenues for the coming quarter and $0.07 on $128.9 million in revenues for the current fiscal year. Investors should be mindful of the fact that the outlook for the industry can have a material impact on the performance of the stock as well. In terms of the Zacks Industry Rank, Internet - Software is currently in the top 44% of the 250 plus Zacks industries. Our research shows that the top 50% of the Zacks-ranked industries outperform the bottom 50% by a factor of more than 2 to 1. Riskified (RSKD), another stock in the same industry, has yet to report results for the quarter ended June 2026. The results are expected to be released on August 12. This provider of fraud-prevention services is expected to post quarterly earnings of $0.03 per share in its upcoming report, which represents a year-over-year change of +50%. The consensus EPS estimate for the quarter has remained unchanged over the last 30 days. Riskified's revenues are expected to be $88 million, up 8.6% from the year-ago quarter. Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report Blend Labs, Inc. (BLND) : Free Stock Analysis Report Riskified Ltd. (RSKD) : Free Stock Analysis Report This article originally published on Zacks Investment Research (zacks.com). Zacks Investment Research

Interested in Blend Labs, Inc.? Here are five stocks we like better. Blend Labs beat Q1 guidance with revenue of $30.8 million, up 15% year over year, and non-GAAP operating income of $4.1 million. Mortgage suite revenue rose 18% and consumer banking revenue increased 12%, while the company also ended the quarter with $59 million in cash and no debt. Autopilot is emerging as a major growth driver after its beta launch, with 65 lenders activated, 22 live in production, and more than 7,000 applications touched. Blend plans to begin charging for the AI product at the end of June and said it could support 10% to 15% incremental top-line growth in 2027. Second-quarter guidance remains cautious because of higher mortgage rates and softer refinancing conditions. Blend expects revenue of $32 million to $34 million and warned that 2026 market share could face a roughly 100-basis-point headwind from volume roll-off at one large customer. Blend Labs (NYSE:BLND) reported first-quarter 2026 results above its guidance ranges, as management highlighted growth in its mortgage and consumer banking businesses and outlined an expanded artificial intelligence strategy centered on its Autopilot product. On the company’s earnings call, Nima Ghamsari, Blend’s co-founder and head of Blend, said first-quarter revenue and non-GAAP operating income both came in ahead of expectations. He also pointed to 15 new deals and expansions signed during the quarter, including an eClose deal with a top 20 bank and a new mortgage deal with another top 100 bank. → Light Speed Returns: Corning Cashes In on NVIDIA Growth Ghamsari said Blend’s pipeline as of March 31 was up more than 40% year over year, excluding the pipeline associated with Autopilot, the company’s AI agent and orchestration layer for lending workflows. Jason Ream, Blend’s head of finance and administration, said total revenue for the first quarter was $30.8 million, above the high end of the company’s guidance range and up 15% from a year earlier. He said growth was driven by both mortgage and consumer banking. → Uber's Annual Product Showcase Reveals It Is Coming for Airbnb and Booking Mortgage suite revenue was $17.2 million, up 18% year over year. Blend processed approximately 187,000 funded loans on its platform during the quarter, up 29% year over year and slightly above the company’s expectations entering the period. Ream said the higher loan volume was partially offset by lower year-over-year economic value per funded loan, which was $84 in the quarter. He said that figure was within the $84 to $85 range discussed on the company’s prior call, but at the lower end because higher mortgage volumes mechanically reduce the per-loan calculation under some fixed-fee customer arrangements. → Wells Fargo’s Comeback Is Real—But Not Risk-Free Consumer banking suite revenue was $10.8 million, up 12% year over year. Professional services revenue was $2.9 million, up from $2.1 million in the fourth quarter. Ream said about $600,000 of the professional services revenue related to work completed in prior periods and recognized in the first quarter under the company’s revenue recognition policies, adding that Blend does not expect a similar catch-up amount in future quarters. Blend reported non-GAAP gross profit of $24.8 million and a non-GAAP gross margin of 80.3%, up from 72.9% in the first quarter of 2025. Ream said the quarter’s gross margin benefited from the professional services catch-up and a one-time cost-of-revenue benefit that together added about 2 to 3 percentage points. Non-GAAP operating income was $4.1 million, above the company’s guidance range of $2 million to $3 million, representing a non-GAAP operating margin of nearly 13%. Free cash flow was $7.3 million, compared with $15.5 million in the prior year. Blend ended the quarter with $59 million in cash, cash equivalents and marketable securities and no debt. The company also repurchased 11.2 million shares during the quarter at an average price of $1.66 per share, deploying $18.6 million of the $50 million authorization announced on its previous earnings call. Management devoted much of the call to Autopilot, which Ghamsari described as Blend’s flagship AI agent. The company introduced the product in beta roughly two months before the call and allowed customers to use it free during the second quarter. As of May 4, Ghamsari said 65 lenders had activated Autopilot, 22 were running it live in production and more than 7,000 applications had been touched by the product since it moved into live production. He said early results showed improvements in cycle time and conversion rate. Ghamsari said two of Blend’s largest lenders were actively implementing Autopilot with go-lives planned for the second quarter, and that three more top 20 logos in Blend’s net-new pipeline could be influenced by the product. He said the company already had $10 million in Autopilot-related pipeline. “This is not a small incremental line item for us,” Ghamsari said, describing Autopilot as “a whole new leg of growth” on top of Blend’s existing mortgage and consumer banking suites. Blend plans to move Autopilot to paid tiers starting at the end of June. Ghamsari said some base AI-enabled capabilities will be included in Blend’s workflow, while paid tiers will include what the company calls “underwriting intelligence,” where Autopilot reads documents, takes action on loan files, runs calculations, reconciles information against guidelines and advances work through the lending process. Over time, Blend intends to move paid Autopilot tiers to a per-funded-loan model, similar to the rest of its mortgage suite. Ghamsari said that structure aligns Blend’s revenue with customer success when lenders fund more loans. Ghamsari said Blend sees a path for Autopilot and internal AI initiatives to drive 10% to 15% incremental top-line growth in 2027, along with greater efficiency and speed inside the company. In response to a question from Ryan Tomasello of KBW, Ghamsari said that view is supported by the current $10 million Autopilot pipeline and early customer momentum, while noting that the company still has “a lot of work” ahead. Blend is also using AI agents internally through what Ghamsari called “Blend Background Agents.” He said the goal is for agents to take the first pass on outside inputs such as support tickets, customer issues or feature requests before a team member reviews and approves the work. Ghamsari said the company’s AI adoption efforts have already resulted in more than 1.5 times productivity in 2026 versus 2025 based on the number of pull requests from the engineering team. For the second quarter, Blend expects total revenue of $32 million to $34 million, representing year-over-year growth of approximately 1% to 7%. The company expects mortgage suite revenue to grow 4% to 10% year over year, with economic value per funded loan in the $79 to $80 range. Consumer banking suite revenue is expected to range from a 2% decline to 4% growth year over year in the second quarter. Blend guided for non-GAAP operating income of $5.5 million to $6.5 million, implying a non-GAAP operating margin of approximately 18% at the midpoint. Ream said Blend’s 2026 mortgage market outlook is anchored to Fannie Mae’s updated forecast, which calls for total mortgage market growth of approximately 19% year over year but was reduced earlier in the month as mortgage rates moved higher. He said Blend will remain cautious until rates decline meaningfully and refinancing activity improves. Ream also said initial 2025 HMDA data showed approximately 4.4 million originations for the year, putting Blend’s 2025 mortgage market share at about 17%, within the company’s prior 16% to 18% guidance range. For 2026, Blend expects a market share headwind of about 100 basis points, primarily due to volume roll-off from one large customer previously discussed by management. Management said Autopilot revenue upside is not yet included in the company’s expectations. Ream said Blend hopes to provide more detail on the potential impact after the free trial period and more time with customer usage data. Blend Labs, Inc operates as a financial technology company that offers a digital consumer banking platform designed to simplify and automate the lending and account opening processes for banks and credit unions. Its cloud-native software enables financial institutions to deliver a more seamless customer experience by consolidating multiple steps—such as application intake, identity verification, document collection and underwriting—into a unified digital workflow. Blend's platform is built to integrate with existing core banking systems and third-party data providers, allowing clients to accelerate loan origination and deposit account opening while maintaining compliance and security standards. The company's product suite includes solutions for mortgage origination, home equity lending, consumer personal lending and deposit account opening. This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest reporting and unbiased coverage. Please send any questions or comments about this story to [email protected]. The article "Blend Labs Q1 Earnings Call Highlights" was originally published by MarketBeat. View MarketBeat's top stocks for May 2026.

Image source: The Motley Fool. Thursday, May 7, 2026 at 4:30 p.m. ET Head of Investor Relations — Meg Nunnally Cofounder and Head — Nima Ghamsari Head of Finance and Administration — Jason Ream Meg Nunnally: Good afternoon, and welcome to Blend Labs, Inc.'s financial results conference call for 2026. I'm Meg Nunnally, Blend Labs, Inc.'s head of investor relations. Joining me today is Nima Ghamsari, our cofounder and head of Blend Labs, Inc., and Jason Ream, our head of finance and administration. Before we start today's call, I'd like to note that we refer to certain non-GAAP measures which are reconciled to GAAP measures in today's earnings release and in the appendix of our supplemental slides. Non-GAAP measures are not intended to be a substitute for GAAP results. Unless otherwise stated, all financial measures we will discuss today, including our profitability, refer to non-GAAP. Also, certain statements made during today's conference call regarding Blend Labs, Inc. and its operations, in particular, our guidance for 2026, other commentary regarding 2026, and our expectations about markets, our strategic investments, product development plans, and operational targets may be considered forward-looking statements under federal securities laws. We caution you that forward-looking statements involve substantial risks and uncertainties, and a number of factors, many of which are beyond the company's control, could cause actual results, events, or circumstances to differ materially from those described in these statements. Please see the risk factors we have identified in our most recent 10-K for fiscal year 2025 and our other SEC filings. We are not undertaking any commitment to update these statements if conditions change, except as required by law. The financial information presented on this call is based on continuing operations, and prior periods have been recast to operations that are now discontinued. Lastly, we will be providing a copy of our prepared remarks on our website by the conclusion of today's call, and an audio replay will also be available soon after the call. I will now turn the call over to Nima. Nima Ghamsari: Thanks, Meg, and welcome, everyone. It has been a whirlwind two months since our last call. We reported our Q1 numbers today, which Jason will spend time on, but we came in higher on revenue and non-GAAP operating income than expected. We also signed 15 new deals and expansions in the quarter, including an e-close deal with a top 20 bank along with a new mortgage deal with another top 100 bank. Our pipeline as of March 31, 2026 is up more than 40% year over year, and that does not include Autopilot pipeline, which I will cover in a minute. But the world has shifted underneath us in those two months: increased global conflict, inflation, and rising mortgage rates, and that leads me to be a little conservative in the short-term numbers. But I am incredibly optimistic about the future. My optimism comes from two things, and they are both tied to artificial intelligence. The first is Autopilot, which is our AI agent and orchestration layer that we put right alongside our customers' work as they work with consumers. The second is the agents we are building inside Blend Labs, Inc., which are starting to do our own work. Together, I believe these two pillars give us a path to see 10% to 15% incremental growth already for us in 2027 on the top line, and more efficiency and speed as a company internally. Let's start with Autopilot. For those new to the story, Autopilot is our flagship AI agent. We unveiled it and rolled it out in beta almost exactly two months ago, telling our customers they could use it for free and try it out for all of Q2 to see it in action and help their business. As of Monday, May 4, 2026, 65 lenders have activated Autopilot, 22 are running it live in production, and over 7,000 applications have already been touched by Autopilot since we moved it to live production. And we are seeing their early results are improving, both in cycle time and in conversion rate. Two of our largest lenders are actively implementing Autopilot right now with go-lives planned for Q2, and we have three more top 20 logos in our net new pipeline that we expect Autopilot to be a meaningful catalyst for closing those new logos, in total already sitting on $10 million in pipeline, because it solves a real problem for our customers and the consumers they serve. But the more important story for me and for our company, for our customers and our shareholders, is how quickly that product is evolving. We have been publishing details on our blog every week, and there are two that I want to call out. The first is Autopilot Chat. That was rolled out about a month ago, a conversational interface where the borrower can ask Autopilot questions about their loan in plain language as they are going through the process: what documents are still needed, why we asked for a specific thing, why it matters to their situation, what happens next. Instead of a static task list or making a phone call, the borrower can have a real contextual understanding of what is going on to help them through the process. This is the kind of interaction that consumers are starting to expect, and we are right on top of it. The second is something I am even more excited about, which is Autopilot MCP. That opens up the Blend Labs, Inc. platform so that our customers can build their own agents on top of Blend Labs, Inc. or use Blend Labs, Inc. in a headless way in their existing workflows, and still get the benefit of all the compliance, all the data model, the workflows, all the native integrations we built, and the intelligence layer of Autopilot. One of our large mortgage company customers has already built a voice agent using it, and I am seeing this as really important and really promising for our customers who want to own more and more things they can do but move really fast. And that pattern—customers innovating with us and around us, rather than instead of us—is exactly what we want and exactly what we expect to see more of going forward. What this all adds up to is something I think is really powerful: our customers can now see a path from initial borrower touch all the way to clear to close without a team member ever having to touch a file. They still can work on the file, but they will not have to. That is fundamentally different value than we could ever offer before or the industry could ever offer, and something that I dreamed of being able to offer when I started the company in 2012, and now agentic AI has made that dream possible. And on top of that, eight weeks in, we are shipping at a cadence that Blend Labs, Inc. of years ago and most enterprise software companies would measure in quarters, and every one of those updates is grounded on what our customers need, what they are telling us they want, and how we can help impact and improve their business. With adoption well underway, let me give you an update on how we are going to monetize this. Autopilot has been in preview to date, and our priority has been getting real customers live and proving the value. Starting in June, we are going to move to paid tiers. Now, just like any modern software company, there is going to be some base capabilities built into our workflow that provide intelligence, like “did you upload the right document?” and that is useful. That is going to lower some friction for consumers to get started and understand AI. But the paid tiers are where the full product lives—what we call underwriting intelligence—where Autopilot is reading the documents, taking real action on the loan file, running calculations, reconciling its guidelines, and driving the work forward. Over time, our intent is to move the paid tiers of Autopilot to a per funded loan model, just like the rest of our mortgage suite. It is the right long-term structure, and our customers like that because it allows them to see and track the value on a per-loan basis, and we get paid when they make a successful loan. That is a great product for us, it is a great alignment for us with our customers, and it incentivizes us to make sure this is providing real loan-level funded value improvements. When Autopilot helps a lender fund more loans with the same number of people, our revenue scales with their success, not with their headcount, and that is how we have always built Blend Labs, Inc., and that is even more important today in an agent-first world. We are going to continue to provide updates on Autopilot as more customers sign on, but I want investors to understand this is not a small incremental line item for us. Autopilot is a whole new leg of growth for the company on top of the great mortgage and consumer banking suites that are already growing, and we plan to keep growing it. Before we move off Autopilot, I want to spend a minute on something that I think is really important and I keep getting asked about from investors. The billion-dollar question is: where does the durable value in enterprise AI actually accrue? This is an ongoing debate, and it is important to understand where Blend Labs, Inc. fits and how I see this. For the last couple of years, the focus of the industry and the world broadly has been on the foundation models: which model is the fastest, the smartest, the best in benchmarks, the cheapest. That focus is understandable, but as models converge in capability and keep innovating, the durable value is shifting up the stack to the orchestration layer between the model and the workflow—to the area that people call the harness—and the thing that is driving actual end business outcomes. The harness, to put it clearly, is a system that channels the engine and all the tools around it into a reliable, controlled outcome, which is so important for an industry like ours, like financial services. And the data and the documents and the specific context of any moment is the fuel that makes any of that work actually useful. Autopilot is exactly that. It is not a model. In Autopilot, we use the best available models underneath. Instead, it is the orchestration layer that decides what to do given that exact moment in a loan: it retrieves the specific guidelines, gets the full context of the loan, runs the right calculations, validates the outputs against investor and regulatory requirements, updates the loan file, and triggers the native Blend Labs, Inc. workflows that move the file forward. That logic is specific to that exact loan and exact consumer in front of it, and it is the kind of work that generic AI is not built to do. It needs a system around it, and that is where Autopilot fits in. Autopilot MCP just takes that to the next level. It allows the Blend Labs, Inc. platform users to build their own agents or even work with Blend Labs, Inc. in a completely headless way, which means the harness becomes a platform for them to move really fast because they get all the regulation, the compliance, the integrations, and the Autopilot intelligence out of the box, and they can build their own experiences and their own agents around that. That is a meaningfully different level of importance because now you become more of the engine—the powered by—instead of the interface, and that is where agents can be really powerful. That compounds more as we open up more capabilities for our customers to build faster and on top of us. That is why I get more confident every quarter about where Blend Labs, Inc. sits in the AI landscape. We are the vertical industry harness for origination. We have the proprietary data to make that harness work. We have the business model already to help capture the benefit of automation and still give most of our benefit to the customer and, hopefully, the consumer. That is the durable place to be. That is why I am excited—that is where Autopilot is. We are bullish on our first pillar, which is agents for our customers. But I am even more bullish on our internal work—how we are using agents there. Over the last few months, we have been building something that we are, boringly, calling Blend background agents. It is not a new idea, but it is a simple idea: anytime we get an input from the outside world—it could be a ticket, a customer issue, a feature request—before that reaches a team member, we want an agent to take the first pass of that work and take action on that, and the team member reviews and approves it. In practice, that could be something like a ticket comes in outlining a bug in our system; an agent immediately picks it up from our support queue, looks at it, identifies the bug, writes the code to fix the bug, tests the code to make sure the bug is now fixed, and then sends it to a human and says, “Hey, I changed these 10 to 50 lines of code. Can you approve this?” That moves our team from manually driving the car and making the turns and figuring out how to get from A to B, to playing air traffic control with, hopefully, dozens of cars. To support that, we have given our agents access to our internal tools, our entire code base, the ability to stand up environments, and they will now take a first pass before our engineers or our support team ever see that issue. When I look at the numbers, the new process of how we are adopting AI at Blend Labs, Inc. has already resulted in more than 1.5x productivity in 2026 versus 2025 based on the number of pull requests our engineering team is doing, and we are just getting started. Prospects and customers are already taking notice of how fast we are moving. I get notes from customers all the time, and I have been on-site with our biggest customers in the last month, and I can tell you that momentum is palpable. Our customers have noticed a change in our quality and speed. I want to be clear: this is not a one-team experiment. This exact same pattern of agents doing the first pass of work should apply to every role in every company, and specifically at Blend Labs, Inc., it will apply to roles here. That could be something like onboarding a new customer, preparing a cut for a customer business review or when we are going on-site with them, or even something as esoteric as getting a manual Excel worksheet that outlines what loans have been funded—having our accounting team’s work done before our accounting team even has to pick it up. I said on the last call that we aim to be in the top 1% of all companies in terms of agentic AI adoption, and I really meant it. We are going to do it. It is something I am very passionate about, and we are going to keep driving for that. When done, I believe this effort combined with Autopilot creates the path to 10% to 15% more top-line growth and a lot more efficiency and speed for us, and that speed is probably the most important thing for any business and especially for a company like Blend Labs, Inc. It means more customer issues fixed, more great features developed, more things like we have done with Autopilot, continuing to grow Autopilot, faster time closing a quarter, better preparedness for customer business reviews—these will be the new Blend Labs, Inc. To wrap up, transforming a company of our size into an agent-first company is definitely more work and more complicated than the world understands, but it is worth it. We have a really important mission. Our customers serve millions of consumers across the country every single year, so this change cannot come fast enough. We are taking it as fast as we can, and we feel like, to be quite candid from my perspective, we are the best-positioned company in the space. It is something that I spend a lot of my time on, and the team is even more passionate about. So while war and tariffs and oil and all those things might create some conservatism around short-term mortgage market numbers because the macro and the rollout time for what we are building also take some time, I have never been more energized about the medium term and, hopefully, even the long term for our customers, our team, and our investors. I will now turn the call over to Jason Ream for the financial results. Jason Ream: Thanks, Nima, and thank you to everyone else joining us on the call. We delivered a strong start to 2026, with both revenue and non-GAAP operating income above the high end of our guidance ranges. Revenue grew 15% year over year, and our non-GAAP operating margin expanded to 13%, reflecting growth across the business and reflecting the operating leverage we have continued to build into the model. Total revenue in Q1 2026 was $30.8 million, above the high end of our guidance range, driven by growth in mortgage and consumer banking alike. Mortgage Suite revenue was $17.2 million, up 18% year over year. Funded loans on our platform were approximately 187,000 in Q1, up 29% year over year and slightly better than we had assumed coming into the quarter. That strong volume growth was partially offset by a lower year-over-year economic value per funded loan, which came in at $84 in Q1, within the $84 to $85 range we discussed on our last call. We were at the lower end of our range primarily because of higher mortgage volumes, which lowers the per-loan economics calculation given some of the fixed-fee arrangements that we have within our customer base. Consumer Banking Suite revenue for the first quarter was $10.8 million, up 12% year over year and consistent with the color we shared on our last call. Professional services revenue for the first quarter was $2.9 million, up sequentially from $2.1 million in Q4. Of the $2.9 million in professional services revenue, approximately $0.6 million related to work completed in prior periods that was recognized this quarter under our revenue recognition policies. We would not expect a similar catch-up amount in future quarters. Turning to profitability, non-GAAP gross profit was $24.8 million and our non-GAAP gross margin was 80.3%, up from 72.9% in 2025. I would note that gross profit in the quarter benefited from the PS catch-up that I just mentioned, as well as some one-time cost of revenue benefit that together brought gross margin for the quarter up by about two to three points. Please keep that in mind as you think about modeling gross margin going forward. Non-GAAP operating expenses were $20.7 million in Q1, up 10% year over year. As a reminder, the year-over-year comparison reflects the change in our internally developed software capitalization methodology that we discussed last quarter, where we are capitalizing less of our R&D personnel cost than we did in 2025. This is an accounting treatment change rather than a change in the nature of our R&D investment. As a result, reported R&D looks elevated on a year-over-year basis, an effect that will persist to some extent in 2026 until we lap prior-year periods. Non-GAAP operating income was $4.1 million, above the high end of our $2 million to $3 million guidance range and representing a non-GAAP operating margin of nearly 13%, an improvement of approximately 10 points compared with 2025. Free cash flow for the quarter was $7 million compared to $15.5 million in the prior year. We are pleased with the strong cash flow generation and want to remind you of our seasonal patterns, where Q1 is typically a strong collections quarter in our business. Our balance sheet remains strong. We ended the quarter with $59 million in cash, cash equivalents, and marketable securities, and zero debt. Putting our cash to work, we repurchased 11.2 million shares during the quarter at an average price of $1.66 per share under our share repurchase program, deploying $18.6 million of the $50 million authorization we announced on our last call. As we said last quarter, this program reflects our conviction in the long-term value of the business and our commitment to disciplined capital allocation. With zero debt and a solid liquidity position, we have the balance sheet to invest in both the business and in our shareholders simultaneously. Before I turn to outlook, I want to spend a moment on market share and on the macro environment. On market share, the initial release of 2025 HMDA data in early April showed approximately 4.4 million originations for the year, which puts our 2025 mortgage market share at approximately 17%, squarely in the middle of the 16% to 18% range we guided to back in November. The HMDA data will continue to settle as late filings come in, but we do not expect that figure to move meaningfully. As we look into 2026, we expect a market share headwind of 100 basis points, primarily reflecting the volume roll-off of one large customer that we have discussed previously. At this time, we do not see any other significant headwinds to our market share. On the macro side, the spring housing market started on stronger footing than many had expected, supported by improving affordability and slowly rebuilding inventory. That said, the recent rise in mortgage interest rates adds uncertainty to the outlook. Fannie Mae's most recent forecast calls for total mortgage market growth of approximately 19% year over year in 2026, but Fannie reduced both its second quarter and full year 2026 outlooks earlier this month as rates have moved higher. Our own 2026 view is anchored to that updated Fannie outlook. We will remain cautious in our outlook until rates come down meaningfully and refi activity picks up. We have the platform and the customer base in place to capture the upside when conditions improve. Now let's turn to guidance. For Q2 2026, we expect total revenue to be between $32 million and $34 million, representing approximately 1% to 7% year-over-year growth. Underneath those headline numbers, we expect Mortgage Suite revenue to grow 4% to 10% year over year, driven by mortgage market volume growth and partially offset by a year-over-year decline in value per funded loan, which we expect to be in the $79 to $80 range in Q2. The decline in EV PFL from Q1 to Q2 is primarily driven by increased volume, which, as I mentioned earlier, mechanically lowers EV PFL. We expect year-over-year Consumer Banking Suite revenue growth to be between negative 2% to positive 4% in Q2. We expect Q2 non-GAAP operating income to be between $5 million and $6.5 million, implying a non-GAAP operating margin at the midpoint of approximately 18%. A few additional notes on what is embedded in our expectations: our Mortgage Suite business continues to be subject to macro volume fluctuations, and depending on the trajectory of mortgage rates and the broader housing market from here, Mortgage Suite revenue could moderate or even flatten out in 2026, particularly if refi activity remains soft. On per-loan economics, Q1 is typically the high watermark due to seasonality, which is why we are guiding to a Q1-to-Q2 step down from $84 in Q1 to $79 to $80 in Q2. In the absence of an uplift from Autopilot—which is too early to quantify and is not baked into any of our expectations—we would expect EV PFL in the second half of 2026 to fluctuate with seasonality but still stay below Q1 levels. On consumer banking, growth is moderating based on the headwinds we discussed on our last earnings call. In addition, we have also seen softer macro-driven volumes on home equity as rates have moved higher. Combining these two factors, we expect single-digit year-over-year growth in consumer banking in the back half of 2026, with Q3 growth likely lower than Q4 given the year-over-year compares. There is macro sensitivity in the home equity portion of our consumer banking business; if rates rise from here, our expectation would be to see additional pressure on those growth rates. Finally, I would like to touch specifically on Autopilot. While we are incredibly excited about the potential for Autopilot to generate revenue upside, we would encourage investors to be cautious about incorporating this into models at this juncture. We hope and plan to provide additional information on potential impact to the outlook as we get past the free trial period and have a little bit more time under our belt. In summary, we feel very good about the shape of the business heading into the rest of 2026. Q1 marked our second consecutive quarter of year-over-year growth in mortgage. With churn now stabilized and the partnership model transition behind us, we expect most of the variability in mortgage revenue from here to be macro-driven. Cost discipline remains intact. We expect to continue to drive additional productivity and efficiency over the year as AI-enabled workflows compound across our internal processes—an effort that, as Nima discussed, is now well underway across the company. This is indeed an exciting time for Blend Labs, Inc. We hope that you are excited to be part of it too. We will now open the call for questions. Operator: Thank you. We will now begin the question and answer session. If you would like to ask a question, please press star 1 to raise your hand. To withdraw your question, press star 1 again. We ask that you pick up your handset when asking a question to allow for optimum sound quality. If you are muted locally, please remember to unmute your device. Please stand by now while we compile the Q&A roster. Your first question comes from the line of Ryan Tomasello with KBW. Your line is open. Please go ahead. Ryan Tomasello: Thanks, everyone. Nima, in your prepared remarks, you mentioned that Autopilot and your AI initiatives present a path, I think, to what you said was 10% to 15% more top-line growth. Can you just put a finer point on what you mean by that, and what underpins your confidence in quantifying the benefits at this stage? Nima Ghamsari: Yeah, great to hear from you, Ryan. I would start with our current pipeline. Our current Autopilot pipeline is about $10 million. We have only been in the market for just over a month now with pricing, and we have a lot of customers who have turned it on and really positive feedback we are getting. I mentioned two very large go-lives with customers. If we can keep up that momentum, think of it as 10% to 15% incremental on top of whatever other growth you may be forecasting, coming from Autopilot. That is what we see a path to right now. We obviously have to keep executing and have a lot of work in front of us, but the product is awesome and our customers love it. Ryan Tomasello: Great. And then maybe just turning to consumer banking. Given the noise in that segment from the large customer churn, maybe you can just help us understand where the underlying revenue growth is running in that business, both for Q1, and then just at a higher level, based on the data points you have given previously about, I think, a $2.5 million impact from that large client in consumer banking. It just seems like the growth profile there is coming in a bit weaker than what was initially hoped for. So, Nima, just your broader commentary around how you feel the strength of that business going forward. Thanks. Nima Ghamsari: I would say the biggest impact is from that large customer, and they had a pretty big consumer banking line item that you called out. On the positive side, we have some good-sized financial institutions going live with our wall-to-wall suite this year. Those rollouts are in progress, and we are excited about that. Once that hits, I think that will be a positive benefit. We also have great customers rolling out our Rapid Home Equity product as we speak, and that will be another positive catalyst for us as that happens. Obviously, the home equity market has other macro things going on, but there are enough new things happening on the consumer banking side broadly that make me feel really good about the consumer banking business. Ryan Tomasello: Great. Thanks, guys. Operator: Your next question comes from the line of Dylan Becker with William Blair. Your line is open. Please go ahead. Dylan Becker: Hey, appreciate it. Nima, I appreciate all the color on Autopilot and Autopilot MCP. It sounds like a lot of customers are interested in piloting. I think you called out some of the early proof points around improved cycle times and conversion rates. I wonder if you could provide a little bit more color on what that looks like relative to a non-automated process to try to tangibly put some value on what customers are seeing and learning, and then maybe how you are also thinking about the deployment or utilization of the first-party agents versus some of the MCP-enabled agents, and maybe the economic variability between those? Thank you. Nima Ghamsari: Yeah. So on the impact, there are two anecdotes I will share for two of the customers who have been the biggest users of it. We help them track the cycle time and the conversion. The conversion is less obvious why it improves, and I actually talked to one of our customers about this; I will get to that in a second. The cycle time with one of the customers, for example, from application complete in Blend Labs, Inc. to closing disclosures being sent to the customer, went from 29 to 21 days. That is a pretty meaningful improvement in their cycle times. It makes sense fundamentally because customers have a lot of back and forth with consumers, and what Autopilot does is, in real time as the consumer is in the flow, it finds those things that are going to be the gotchas down the line. It shows the consumer, “Hey, we noticed that this account is in the name of a trust. We need to get your trust documentation right now,” versus asking for it a few days later once an underwriter reviews it and sends it to a processor, which sends it back to the loan officer. It short-circuits the process in a positive way. Our hope with Autopilot plus some of the Rapid products—you put those two things together, I will call it Rapid Pilot—you can get an application started, approved (because Rapid gives you an approval and an offer up front), and then once that customer is ready to go, get them clear to close in a matter of minutes. That is the world we want to enable for our customers, or maybe conditionally clear to close on an appraisal if there is an appraisal necessary for a mortgage. Those are positive numbers. Where I have been more surprised is why the conversion is so much better, but I guess it makes sense—when you can give people more certainty, faster, we are seeing good conversion uplift too. It is early, but that is even more valuable to our customers because those are consumers that would be walking out the door that you have spent time and money on as a lender, not just on things like credit pulls and other data pulls, but also your team's time and energy. As we can shorten these cycles and make the process of lending more real time, it fundamentally transforms the industry. One thing I wanted to say about consumer banking—because we are in the process of building out the integrations to all the consumer banking products for Autopilot—there is opportunity there now. There are fewer manual tasks in consumer banking, but there is a lot more volume of those tasks in terms of number of units these customers do. While it may not be worth thousands of dollars per loan to our customers long term in consumer banking, or per new account, the scale does matter. They have very big operations teams managing these processes. It is important for them to be able to do a lot more volume with those teams, and I think Autopilot enables that. One of the historical struggles—and I mentioned this in my prepared remarks—is rates really drive refi activity in particular. If you are a mortgage servicer and you have a lot of your volume in refi, your only way to handle large amounts of volume has been to scale up and scale down teams, and you do not get to really predict when rates go down. The ability to create elasticity of workforce—when now you have agents that a lender can spin up and spin down alongside their team before their team is doing the work, with agents taking a first pass—changes the economic profile of servicing and recapture of servicing. For our large servicing customers, which we have many, it is going to change the way that they are able to do business because it will allow them to handle market fluctuations even better than someone on the purchase side. Dylan Becker: Makes sense. Thank you, Nima. And then maybe for Jason as a follow-up to that too. You kind of called out the per-funded-loan dynamics and market share dynamics. I would love to double click—again, if you can remind us, because it sounds like you are actually increasing market share with the customers coming online or being onboarded, but that is kind of working inversely upfront against per-funded-loan volume. So remind us of the mechanics of that, as well as maybe when we would expect that to flip and those two tailwinds maybe work in tandem, to where you see market share growth inflection as well as per-funded-loan expansion over time? Thank you. Jason Ream: Good question, Dylan. We are seeing volume growth. As I mentioned, we had better volume in Q1 than we had expected even coming into the quarter. Part of that is our customers doing better; part of that was the market being a little bit better than we expected in the quarter. Of course, we are always trying to add share and bring new customers onto the platform. As far as per funded loan—putting aside the seasonal variability that comes from the mechanics I talked about—we are doing a much more concerted effort now to drive growth year over year with existing customers. Things like Autopilot give us better pricing leverage coming into new customer situations. Obviously, that drives its own revenue stream, but it also gives us leverage in the core platform as well. Rapid remains a driver as well on the refi side in particular. As Nima mentioned, refi is even more sensitive to rates than purchase, and we do not have a Rapid Purchase product—we have Rapid Refi. As rates come down, we should see a benefit in volume and revenue in that sense, but also as we get more customers up on Rapid Refi, we should see a benefit in PFL as well. Operator: Your next question comes from the line of Joseph Vafi with Canaccord Genuity. Your line is open. Please go ahead. Joseph Vafi: Hey, guys. Good afternoon. Thanks for taking my questions. You might just update us on the Rapid product uptake and how you are seeing market reaction to them? Obviously, the market backdrop is not as strong as we would like, but some of the feedback you are getting? I have a follow-up. Nima Ghamsari: I would reiterate what I said about this Rapid Pilot—that seems to be getting the momentum and focus from our customers. Rapid plus Autopilot together is a lot of what I spend my time on. I have had two on-sites with two very large banks and lenders in the last two weeks about this specific thing that they want to get live in Q2. In practice, our customers want to be able to, especially for refis and home equity, make an offer in real time, and then fulfill the work they need to get done on that offer in real time. The combination of those two things has been incredibly powerful. On top of that, we have some very, very large customers going live with Rapid Home Equity—some of the top home equity originators in the country. It is definitely a good time in the industry. If I had one criticism of myself here, it would be: how do I make this so easy to adopt that they flip a switch and turn it on and now they have Rapid Refi enabled in their environment? I think that is a challenge for us as we go into the next couple of months, and we intend to make that happen. As we make that happen, our customers will be able to adopt it much more easily. That is a key learning for us from the Autopilot rollout, where we made it truly self-serve for a customer to turn on, and we are seeing the adoption. The numbers that we shared—in terms of number of lenders that have turned this on as a percentage of our total—think about large financial institutions turning on a new AI agent for their organization with the flip of a switch, even without calling us. The most surprising part was we had very large banks turning this on in beta and production without us even knowing about it. Then we saw it start to stream through our logs and said, “Oh, we should probably reach out to them and talk to them about it.” We are a product-led growth company. We do like to talk to our customers to help them get the most out of our product, but making things easy to adopt is going to be very good for Blend Labs, Inc. Everything comes back to speed: speed of adoption and speed of iteration for our team. We showed that with Autopilot, and I am confident we can take that micro-culture and product concepts to all the things we do at Blend Labs, Inc. Then we can help fundamentally change the landscape of how our products are used and how they can impact our customers. I will end with one last anecdote. Autopilot MCP has unlocked a lot of doors for us. I was on-site with one fairly large customer last week, and they had their head of engineering in the room. The first thing the head of engineering asked was, “Hey, I want to build this into our mobile app.” I said, “Great. You now have a way to do that. It is called Autopilot MCP. You can get all the capabilities of Blend Labs, Inc., and the intelligence layer of Autopilot, entirely in your own environment.” He said, “Wow, okay,” and his first question to me—which was compelling—was, “Can I use this in other parts of my business? We do not use Blend Labs, Inc. for these other kinds of loans,” and he named a couple other kinds. I said, “Yeah. Sure. Autopilot works. You can put custom guidelines in there yourself. You do not even need to talk to us.” His eyes lit up, and he asked for a copy of the Autopilot MCP documentation, which we sent to him. Those are people who have historically struggled with how to fit themselves and their tech stack into the Blend Labs, Inc. world, and now we have opened that up. We had another interesting sales call with a fairly large bank, and the digital leader came on the call—historically another one that feels a little bit displaced by us sometimes when we are brought in. His first question was, “Can I use this with my current digital stack?” As soon as the answer was yes with Autopilot MCP, he went from probably being a detractor to someone saying, “Oh, wow. This is actually really interesting. Now I can give new digital capabilities. I can help improve my customer experience in a powered-by way” that would take months, if not years, for them to do internally—building agents that are this powerful and complex. So, no, that was not exactly your question, Joe, but I was remembering that as I was talking. Joseph Vafi: Yeah, no. It is an exciting setup for sure. Thanks for that color, and looking forward to progress on that front. Thank you. Operator: A reminder, if you would like to ask a question, please press star 1 now to raise your hand. Your next question comes from the line of Aaron Kimson with Citizens. Your line is open. Please go ahead. Aaron Kimson: Great, thanks for the questions. Nima, in your conversations, how do customers perceive the value that Autopilot is providing today? Do you feel like it is still primarily being thought of as a component of tech budgets, or are financial institutions increasingly open to viewing agentic products like Autopilot as a component of their labor budgets? Nima Ghamsari: It is interesting. Right now, companies are figuring this out as we speak, so they do not know the answer to that exact question. It goes to how we price this in the short term to allow our customers to use it both for a few months free of charge, but even after that, we are going to have flat pricing that is good for us economically and good for our customers, to give them time in the short term to make the right changes they need to make to their processes and their organizations. Long term, they are all aligned to the fact that labor is something that does not need to be scaled up and down with volume anymore. I was having a conversation with the CEO of one of our large customers, and the idea of being able to scale their organization without having to add thousands or more heads is so compelling. It naturally ends up being a labor question. But probably the more important value proposition—as these numbers around conversion rates get set in stone and we have a better understanding—is going to be even more valuable to our customers. There are so many consumers in this country who can benefit from lower interest rates, or equity from their homes, or consolidating debt, and all these things have been historically hard for our customers to capture, and hard for consumers because they have to go through a lengthy process. If we can make it really transparent with something like Rapid and then really automated with something like Autopilot, it is going to change things. It will make it so that consumers will have less friction in this process, and therefore, consumers will do it—and they will do it with our customers. Aaron Kimson: Got it. That is helpful. And then one more. You have been working with financial institutions for a long time now. Can you talk about the appetite for adopting new products faster today than in the past, and how they are thinking about build versus buy—the balance between adopting AI products from AI-native startups versus established software vendors like Blend Labs, Inc.—and then where the frontier labs fit in? I think we are all trying to figure this out for application software in general. Thank you. Nima Ghamsari: We are in an interesting place where a switch flipped sometime in the first quarter of this year, I think February. Our customers started to realize—maybe it was because of all the Anthropic/Claude/code explosion happening in the market—how important of a transformation this was going to be, and they have all put budgets behind AI and AI initiatives because they know it is important. It is important for their customers, it is important for their users, and it is really important for their long-term economics as a business. It can do really powerful things. People are starting to believe that. It is no longer something they felt was a future 2027 or 2028 thing. It is, “I can actually do this now.” The sheer number of our large financial institution customers that have turned these capabilities on their own and are in active discussions with us or in process with us of rolling them out broadly speaks for itself. They do think through how to fit this into their stack. Is it a company like Blend Labs, Inc. that is already driving a lot of their work internally and for their customers? Are they working with Anthropic or OpenAI or some other company in a big project in a consulting-like fashion, or are they working with a small startup? In the Autopilot versus small startup comparison, because we have so much of the workflow happening in our system already—which are natural entry points to invoke and spin up AI agents and then spin them back down—we have a pretty good advantage to help move very quickly for our customers. Our job is to make sure Autopilot is the best product on the market for the exact types of work our customers need to do—in this case, underwriting intelligence like I referenced in the prepared remarks. As long as we do those things, I do not think they are going to go to a small startup. We have to move fast—and we are moving fast—and we have to build a great product. Autopilot is a great product, doing things that a year ago would have seemed like science fiction to our customers. On the labs—large labs like Anthropic and OpenAI—some of that still remains to be seen. I have heard of really great things the labs are doing with a lot of our customers. I think there is so much of the industry that is going to change; the size of the pie is probably a lot bigger than anybody really understands. The labs are not going to go in and try to build something into our workflow so that they can drive value for our customers—I do not think they would—but even if they would, we are already there. We already have it. Speed is very important in adoption. If you have to do a nine- or twelve-month project to get something versus being able to flip a switch, our job is to make that possible. Operator: We have now reached the end of the Q&A session. This concludes today's call. Thank you all for attending. You may now disconnect. 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