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.

Build Production-ReadyHealthcare AI in 8 Weeks

From AI architecture to clinical launch in 8 weeks — PHI-safe, HIPAA-compliant, and built to pass enterprise security reviews from day one.

PHI-safe AI architecture

Compliant model selection

Hallucination mitigation framework

EHR integration & clinical workflows

BAA-ready from day one

Full IP ownership — no lock-in

Get your 8-week AI roadmap in 30 minutes

Share your AI use case — clinical, operational, or patient-facing. We'll map the architecture, compliance path, and timeline to production.

Is this the right solution for you?

I tried an LLM integration and legal shut it down

I don't know which AI models are safe to use with patient data

I have a clear AI use case but no one on my team owns the compliance side

My competitors are shipping AI features and I'm falling behind

My AI works in a sandbox but can't go to production with real patient data

My existing AI isn't passing enterprise security reviews

How we build your AI product 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, define PHI data flows, assess compliance requirements, and design the right architecture before a single line of code is written. We identify which AI models are safe to use, where guardrails are needed, and how to keep PHI protected at every touchpoint.

Deliverables

AI use case definition and scope document · PHI data flow map with risk assessment · Compliant model selection — open-source, private, or fine-tuned · AI architecture design with HIPAA guardrails documented

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.

What you walk away with

By Week 8 you have a production-ready, clinically validated AI healthcare product — everything below is included in the engagement.

PHI-Safe AI Architecture

Compliant model selection with HIPAA guardrails at every layer

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

4-Week Post-Launch Warranty

Any AI behavior issues or compliance gaps fixed at no extra cost

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.

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30–40% faster clinical documentation

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