◆ Industry
AI development for healthcare
We build AI that runs inside real clinical workflows: multi-agent systems for clinicians, medical-records RAG that cites its sources, AI scribing that turns conversations into structured notes, and insurance-eligibility automation. Accuracy, grounding and clinician review are built in, because in healthcare a confident wrong answer is worse than none.
- 0
- citation hallucinations
- 10+
- clinical forms auto-filled
- 4
- agents in one API
What we build
- Clinical multi-agent orchestration (LangGraph over GPT-4o)
- Medical-records RAG with strict citation contracts, so it never invents answers
- AI medical scribing: speech-to-text to structured forms (Deepgram Nova-2 Medical)
- Insurance eligibility automation (X12 270/271 EDI)
- Per-field confidence scoring for clinician review
- Tenant-scoped, encrypted credential handling (AES-256-GCM)
Frequently asked
Do you have real healthcare AI experience?
Yes. We built a clinical multi-agent orchestrator, a medical-records RAG system, an AI scribe and an insurance-eligibility pipeline for a US healthcare product.
How do you prevent hallucinations in clinical answers?
A strict citation contract: the system answers only from grounded records and returns sources, and says "not available" instead of guessing. This eliminated hallucinations on prior-visit data.
Is patient data kept secure?
We design for privacy: tenant-scoped credentials with AES-256-GCM decryption, and deployments that keep data in your environment where required.
Building AI for healthcare?
Production-grade, owned end to end. Usually a reply within a day.