Uploaded reports, prescriptions, referrals, and discharge notes can create useful context, but only when summaries remain traceable and reviewable. TabibAI uses Anthropic models for nuanced document comprehension and OpenAI models for reasoning-heavy summarization — ensuring every output is grounded in the source material.
TabibAI's product direction treats document summaries as draft context for clinicians, not as final interpretation. The hybrid approach combines frontier and open-weight AI models with a medical knowledge layer covering ICD-10, RxNorm, and SNOMED-CT.
The production roadmap prioritizes clear source references, audit trails, and data-retention controls before live clinical use.
Practical product rule
- Keep original files available for review.
- Separate extracted facts from AI-generated wording.
- Label every summary as draft-only.
- Avoid hiding uncertainty or missing data.
Medical note: TabibAI supports documentation and workflow efficiency under clinician supervision. It does not diagnose, prescribe, or replace professional medical judgment.