Clinical documentation infrastructure
Med-AI Clinical prepares structured radiology and laboratory reports from studies your hospital already produces. Every draft goes to a licensed practitioner, who edits and signs it. Nothing reaches a patient record unsigned.
The workflow radiologists already use, with the first pass prepared for them. The signature is enforced by the software, not asserted in a policy document.
An image or lab report is uploaded, or arrives from your existing systems. It is analysed and a structured draft is prepared — findings, impression, coded conclusions.
The draft appears on a reading worklist, oldest first. The reviewer accepts it, corrects it, or rejects it with a reason. Urgent findings are escalated separately until somebody acknowledges them.
Signing attributes the report to a named practitioner with a timestamp. Only then does it become final — including to any system reading it over FHIR.
Most of the work in clinical software is not the model. It is isolation, auditability, consent and interoperability — the questions a hospital's IT review asks first.
Each hospital's data is separated by PostgreSQL row-level security, not only by application code. A missing filter in a query cannot leak another hospital's records.
Every read and write is recorded. The application can append to the audit log and cannot alter or delete it. Six-year retention is enforced in the database.
Patients, observations, diagnostic reports and imaging studies are exposed as conformant FHIR R4 — the same standard India's ABDM is built on.
ICD-10 conclusions and LOINC-coded lab results. A code the system cannot confirm is carried as text rather than asserted as a coding.
Drug-class allergy cross-reactivity, interaction and duplicate-therapy checks, with daily dose ceilings. A contraindication blocks the prescription until a prescriber explicitly accepts it, on the record.
Per-patient consent for research and model-training use, PHI redaction with a stated coverage report, and deployment in Indian data centres.
Healthcare software is bought on trust, and trust does not survive discovering something later. So this is the honest state of the product.
A diagnostic chain or hospital willing to run a paid eight-week pilot on real historical studies. You get the product and a retrospective validation report on your own data. We get the evidence and the clinical direction.
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