B+
Bull case
20%
Probability
Target price
$30.00
+30.8% vs current
NVST
EnvistaDNYSE / Health Care Equipment & Services
Last Price
At close
2026-06-02
AI scenario view
RankAlpha Sentiment AIMost likely
B
Base case
60%
Probability
Target price
$24.54
+7.0% vs current
B-
Bear case
20%
Probability
Target price
$14.22
-38.0% vs current
AI sentiment snapshot
Latest data as of 2026-02-09
Recent news sentiment (30D)
-26.5
Negative
Company
-
Unavailable
Macro
-26.5
Negative
Pulse
-
Unavailable
Sentiment proxy
+51.6
Score
AI commentary
Sentiment is mixed-to-cautious: the consensus median is below the broker_last anchor while a few brokers maintain $30+ targets. Near-term direction will hinge on the upcoming quarterly report and post-earnings analyst reactions; longer-term conviction depends on product execution and consumables growth.
RankAlpha Sentiment AI - 2026-02-09
Open full AI memoEvidence flagged
No evidence quality warning is currently attached to this memo.
Impact
standard
Confidence
-
AI events
2026-05-10catalystNext quarterly earnings report (estimated)High impact
Quarterly earnings and management guidance are the most likely near-term re-rating events; analysts' consensus targets imply downside vs the broker_last anchor which could drive revision risk after results [#SERP-2]. Date follows conservative short-horizon estimate per schema rules.
2026-06-09eventPost-earnings analyst target revisionsHigh impact
Broker and sell-side target changes (e.g., recent Baird update) commonly arrive after reported results and can alter sentiment materially; assume revisions materialize within ~30 days of results [#SERP-9].
2027-02-09catalystProduct pipeline execution and market-share recoveryHigh impact
Sustained upside would require successful commercialization of product initiatives and recovery in dental procedure volumes; this is a multiyear driver that aligns with surveyed analyst upside but depends on execution [#SERP-6].
Recommendation
N/A
No formal recommendation provided.
As of 2026-02-09 • Updated nightlySource: Internal modelMethodology