Medical records show
what happened.
NidaanPath reveals
what is still unresolved.
NidaanPath AI reconstructs fragmented medical records into a live Diagnostic Journey Twin, identifies when diagnostic progress may have stalled, and prepares the missing evidence for safe clinician review.
Diagnostic Journey Twin
Connects consultations, tests, reports, follow-ups and referrals into a live, evidence-linked chronological journey.
Stagnation Detection
Finds unresolved process gaps across multiple healthcare visits using transparent, deterministic Python rules โ not AI guesswork.
Next-Best-Evidence Agent
Asks the single question or requests the evidence that can most improve understanding of the diagnostic journey.
The Problem
Patients with persistent symptoms consult multiple providers. Their journey becomes fragmented across prescriptions, lab reports, referrals, and consultation notes.
Existing platforms store and share records โ they do not reveal whether the diagnostic process is progressing.
The Innovation
- ๐ฌ One Coordinator Agent + 6 controlled tools
- ๐ก 3 Safety Gates โ patient, rules, clinician
- ๐ Deterministic stagnation โ pure Python rules
- ๐ English + Tamil support
- ๐ Clinician escalation packet with PDF
- ๐ฏ Judge Demo Mode โ no API key required
NidaanPath does not diagnose diseases, predict outcomes, recommend tests, prescribe medication, or replace healthcare professionals. It identifies when the process of finding a diagnosis may have stalled and supports safe clinician review. All data shown uses synthetic demo records only.
This is a prototype diagnostic-process continuity system, not a medical device.