Forward-Deployed Clinical AI

Research models, clinical decisions.

Pendentiv is the connective layer between research-validated AI and the clinical decisions it informs. We work as an embedded engineering partner to academic medical centers, shipping real software to real clinicians.

Work with us The approach →
Pl. 01 · Pendentive Section DOME PENDENTIVE PIER Dome on pendentives · The connective structure
01→ Foundation Research, not benchmarks 02→ The Institution Forward-deployed, not shipped 03→ Pendentiv The layer between model & decision 04→ AI Success Adoption over accuracy
The Problem

Built once. Deployed everywhere. Fit to no one.

Clinical AI keeps failing the same way: not on accuracy, but on adoption, trust, and sustained use. A model validated at one institution rarely holds up against another's patients, workflows, and clinicians. The gap was never the model. It's everything between the model and the decision.

81%

Of radiology AI algorithms lost accuracy when validated outside the institution that built them

Yu et al., Radiology: AI 2022
65%

Of US hospitals use predictive AI in the EHR — most never validate it locally for accuracy or bias

Health Affairs 2025 · AHA national survey
88%

Of alerts from a widely-deployed sepsis model were false alarms in external validation

Wong et al., JAMA Internal Medicine 2021
Read the evidence behind this →
The difference · Illustrative

Two ways to put AI in front of a clinician.

Most clinical AI is wired as a reflex: a model re-scores the chart on a fixed clock, checks a vendor-default threshold, and fires an interruptive alert, the same way for everyone. We work the last mile differently, with a layer between the model and the decision that shapes what reaches the clinician and when.

01
Typical

The reflex.

Event-based deployment
fixed clock re-score q15m EVENT lab · vital MODEL threshold ALERT interruptive clinician ! ! overridden same alert · every time · to everyone
  • Re-scores on a fixed clock against a vendor-default threshold. Everyone gets the same alert.
  • One-directional and interruptive. The system never learns the clinician or the moment.
  • A widely-deployed sepsis model missed 67% of cases in external validation;1 up to 73% of alerts are overridden.2
02
Pendentiv

The connective layer.

Workflow-aware delivery
labs vitals notes same fhir events right clinician right time · right form context returns the connective layer local context · human-in-the-loop
  • Same data, same FHIR events, a different last mile.
  • Local context and a human in the loop, inside the tools clinicians already use.
  • One insight, shaped to the person, the moment, and the form it should take.

Illustrative concept — not a depiction of a specific product or vendor workflow. Stage labels (event → model → alert) reflect common real-time EHR deployment patterns.
1 · Wong A, et al. External validation of a widely implemented proprietary sepsis prediction model. JAMA Intern Med 2021;181(8):1065–1070.
2 · Nanji KC, et al. Medication-related clinical decision support alert overrides in inpatients. JAMIA 2018;25(5):476–481.

Where We Work
Event review Care gaps Results & inbox triage Secure messaging Transitions of care Documentation review
See the work →
The Partnership

Built on both sides of the gap it closes.

Pendentiv pairs industry deployment experience with academic decision science. We embed with the researchers and clinical teams of academic medical centers, and with the health systems around them: the one place where the real-world impact of clinical AI can be studied.

Industry deployment

Close to a decade building, deploying, and maintaining machine-learning models inside healthcare, under real constraints and real clinical stakes.

Decision science

Academic rigor rooted in decision-making analysis: judging clinical AI by the decisions it changes rather than the benchmarks it clears.

Meet the partnership →

From bench to bedside.

Whether you have a model that needs building, a grant that needs an engineering partner, or a workflow where AI should land, we'd like to hear about it.

Work with us hello@pendentiv.ai