How do you prevent AI hallucinations in clinical settings?

We build a hallucination mitigation framework as part of the AI Safety Layer (Week 2). This includes output validation against clinical knowledge bases, confidence scoring, human-in-the-loop review triggers for edge cases, and automated monitoring in production. The specific guardrails depend on your use case — a clinical documentation tool needs different safeguards than a patient-facing chatbot.

Can you integrate with our existing EHR system?

Yes. We've built EHR integrations with Epic, Cerner, Athena, and HL7/FHIR-based systems. During Discovery (Week 1) we map the specific data flows and integration points needed for your use case. The integration is built during Weeks 3–6 on top of the validated safety layer.

What if we already have an AI prototype that needs to be made compliant?

That's a common starting point. We audit your existing AI implementation during Discovery, identify compliance gaps, and determine what can be reused vs. what needs to be rebuilt with proper PHI protections. Many founders come to us after legal shuts down their initial LLM integration.

Who owns the AI models and IP at the end?

You do. 100%. All code, model configurations, fine-tuned weights (if applicable), infrastructure, and documentation are fully transferred to you. No vendor lock-in on models or infrastructure.

Clinical AI that survivesthe real world.

Most healthcare AI products pass the demo. Most fail in production — compliance, integration, and scale break them. We build clinical AI systems designed for deployment from day one, not patched for it later.

Workflow-embedded AI — not a chatbot bolted on

PHI-safe model architecture

Hallucination mitigation for clinical use

Auditability + traceability built in

EHR integration & clinical workflows

BAA-ready from day one

Full IP ownership — no lock-in

Map your clinical AI system in 30 minutes

Tell us your use case. We'll map your PHI data flows, model architecture, and compliance path — before you write a line of code.

What breaks in production AI

Inconsistent outputs across clinical workflows

Hallucinations under real-world edge cases

PHI exposure through unsafe model usage

Latency and cost explode at scale

Systems fail enterprise security review

Most teams discover these problems after launch. We design for them from day one.

Category shift

We don't build features. We build AI systems.

Most dev shops build AI features and hand them over. We build the underlying system — the orchestration layer, the data foundation, the compliance infrastructure — that makes AI viable in a real clinical environment.

Workflow-Embedded AI

AI lives inside the clinician or patient workflow — not as a chatbot bolted onto the side.

Data-First Architecture

Structured, longitudinal data is the foundation — not an afterthought scraped from prompts.

Trust & Compliance Built-In

HIPAA, BAA-readiness, auditability and PHI safety are designed before any code is written.

Cost-Aware AI Systems

Routing, caching and model selection make production AI economically viable at scale.

Hero layer

AI Safety Layer — built before the product.

Trust isn't a wrapper. It's the foundation.

Hallucination mitigationGuardrails for clinical usePHI-safe model architectureAuditability + traceability

Every engagement begins with the safety layer — before any product code is written. This is what separates a clinical AI system from a demo that fails in production.

How we build your clinical AI system in 8 weeks

A structured, phased approach — from understanding your AI use case to deploying a production-ready, HIPAA-compliant system. Every phase has clear deliverables and defined outcomes.

Goal

Map your AI use case, PHI data flows, and compliance requirements. Define which models are safe, where guardrails are needed, and how the system — not just the feature — should be architected.

Deliverables

AI system architecture design (not just feature scope) · PHI data flow map with risk assessment · Compliant model selection — open-source, private, or fine-tuned · Cost and latency model for production scale · Data layer design — structured, longitudinal patient data

Outcome

A clear, agreed AI architecture your team, investors, and legal counsel can review — with compliance built in from the design stage, not the deployment stage.

Format

2–3 discovery sessions with your team to map use cases, data structures, and compliance requirements before any build begins.

Where we play

Clinical AI categories we build for.

Intake & Triage

Front-door routing, symptom intake, eligibility and prior-auth automation.

Decision Support

Clinician-facing AI that surfaces evidence, refines notes, and flags risk in real time.

Remote Monitoring

Streaming data, anomaly detection, and intervention loops for chronic and post-acute care.

Patient Engagement

Workflow-embedded conversational AI for adherence, education and care navigation.

Data Infrastructure

Structured, longitudinal data layers that make every other AI product possible.

By Week 8, you have a system — not a demo.

Everything below is engineered as one system and included in the engagement.

An AI system, not an AI wrapper

Orchestration, routing, retrieval and guardrails — engineered as one system. Not features bolted onto an LLM call.

PHI-Safe AI Architecture

Data flows, model selection and storage designed around HIPAA from day one — not patched after legal review.

Production AI Product

Full feature set — agents, workflows, EHR integrations — production-ready

Hallucination Mitigation

Safety framework preventing AI from generating harmful clinical outputs

Clinical Validation

AI behavior tested against real clinical workflows and edge cases

Compliance Documentation

BAA-ready documentation, audit trails, and enterprise security posture

Built for serious healthcare AI teams.

Founders

Shipping your first clinical AI product — and want a foundation that survives V2.

Startups

Past V1, scaling into production, and need to move from prototype to system.

Health systems

Modernizing clinical and operational workflows with AI that integrates, not isolates.

Research teams

Turning models, papers and pilots into deployed, compliant, productized systems.

After 8 weeks

The engagement doesn't stop at launch. The first 4 weeks are covered under full warranty, then you choose what happens next.

4-Week Post-Launch Warranty

Any AI behavior issues or compliance gaps that arise in the first 4 weeks after go-live are fixed at no extra cost. You launch with confidence.

Healthcare Startup Acceleration

After the warranty period — continue shipping on our monthly AI + human subscription. Submit any task (features, fixes, AI work, compliance) and we deliver in 24–48 hours. Month-to-month, pause or cancel anytime.

Trusted by healthcare founders

“

We came in with a bold vision and a very aggressive timeline, and not only did they deliver — they exceeded our expectations at every stage. By Week 2, we were already demoing the platform to prospective customers, and we signed our first B2B contract before development was even complete.

Brittany Fadiora

CEO, Doulio AI

Prototype in Week 1First B2B contract before launchProduction-ready in 8 weeks

cRead full review on Clutch

Questions founders ask before starting

It depends on the use case. We evaluate open-source models, private models, and fine-tuned models for each project. The key criteria are: PHI safety (can the model be deployed without sending patient data to third parties?), clinical accuracy, and enterprise security compliance. We'll recommend the right model architecture during the Discovery phase.

Relevant Case Studies

Clinical AI8 weeks engagement

Thymos Health — AI Medical Chatbot for Conservative Care

PHI-safe RAG-powered AI chatbot integrated with Oyster EHR — scoped patient data retrieval, emergency detection with auto-escalation, and full HIPAA-compliant AWS infrastructure. Real patient data in production.

BAA-ready, passed enterprise security review

View case study →

Clinical AI1+ year ongoing partnership

CareCortex — End-to-End AI Operating System for Healthcare

AI workflow layer integrated with existing EHR — real-time clinical decision support, AI-assisted note generation, routine task automation, and seamless data access. PHI-safe from day one.

30–40% faster clinical documentation

View case study →

Behavioral Health & Wellness8 weeks engagement

AI-Powered Life Planning Platform

AI-powered platform covering healthcare directives, estate planning, and digital legacy. Step-by-step guidance tailored to personal, cultural, and legal contexts — with secure document storage and sharing.

10,000+ families served

View case study →

Explore our core solutions

Already have a working product? These solutions build on the same system-first foundation.

8-Week HIPAA-Compliant MVP Launch

From idea to production-ready, HIPAA-compliant healthcare MVP in 8 weeks — with AI features built in from day one.

Explore this solution →

Healthcare Startup Acceleration

Keep building. Keep shipping. A monthly AI + human subscription with an unlimited task queue and 24-hour delivery.

Explore this solution →

12-Week MVP to Enterprise-Ready

Turn your working MVP into an enterprise-ready platform — SOC 2, HITRUST, and FHIR integrations that unlock hospital deals.

Explore this solution →

Get Started

Healthcare AI doesn't fail at ideas. It fails at deployment.

Most teams can build AI. Very few can deploy it into real healthcare environments. Book a 30-minute architecture + compliance session — we'll map your use case, PHI data flows, and the path to production.

See Our Work