Evidence-grounded medical intelligence

Where evidence
meets intelligence.

Evidenceo builds the intelligence layer for clinical practice — a cited encyclopedia, a doctor-facing evidence agent, and hospital deployments. Built for medicine, from first principles, in India.

Every claim carries its sourcesNMC-verified accessSelf-hosted, end to end
clinic.atlas · live

Ask a clinical question.
Get an answer you can follow to the source.

The doctor-facing agent drafts an answer, grades what's missing, and goes back for the evidence it's short on. Click any citation and land on the exact page of the exact reference — not a bibliography. And when there's no evidence, it says so.

  • Cited, streamed answers
  • Live reasoning trail
  • Image + PDF understanding
  • In-line clinical calculators
  • Conversation memory
Ask Atlas · evidence agent
  1. Retrieve
  2. Rank
  3. Ground
  4. Cite

Baseline before starting: thyroid and liver function, a chest radiograph, and a review of QT-prolonging or interacting drugs.1

During therapy: periodic TFTs and LFTs, ECG for QT and bradycardia, and pulmonary review if new dyspnoea or cough appears.2

In reduced EF, amiodarone is generally preferred over agents with greater negative inotropy for pharmacologic rate/rhythm control.3

High confidence · 3 sources
1 ICMR Standard Treatment Guidelines2 Atlas monograph · Amiodarone · TDM3 CDSCO package insert
The problem

Medicine is drowning in information.

Doctors, students and researchers face the same signal-to-noise crisis in three different rooms. Evidenceo is the layer that clears it — without ever inventing an answer.

01

Clinical practice

  • Information overload
  • Time-critical decisions
  • Fragmented evidence
02

Medical education

  • Passive learning
  • One-size-fits-all
  • No personalisation
03

Antimicrobial stewardship

  • Local resistance patterns
  • Guideline sprawl
  • Bedside time pressure
The ecosystem

Four surfaces.
One evidence backbone.

Atlas, clinic.atlas, the Hinduja guide and Isaac share one corpus and one retrieval engine — so practice, education and stewardship finally speak the same language.

Atlas

The cited medical encyclopedia.

A members-only encyclopedia compiled from cited primary sources. Every claim links back to the exact page of the exact reference — not a bibliography at the bottom.

  • Per-claim citations to raw PDFs
  • Postgres full-text + trigram search
  • Cross-reference graph
  • Grounded diagrams
  • 37-section drug monographs
Open Atlas
How it works

Nothing is written by the model just generating.

Every page is a contract-gated agent call with a separate verifier pass, and safety-critical claims wait for a clinician. The wiki is additive on immutable raw sources — a librarian who writes index cards, never replacing the books.

Stage 1

Ingest

A source PDF is added append-only. Raw sources are immutable — removing one reverse-ingests every page that leaned on it.

Stage 2

Write

Every wiki write is a contract-gated agent call, never free generation. Each factual sentence must anchor to a source or it does not ship.

Stage 3

Verify

A separate verifier agent, with a clean context, re-checks the work before anything publishes. “Looks done” is not a completion signal.

Stage 4

Review

Safety-critical claims — dosing, contraindications, interactions, adverse effects — are held for a clinician to sign off. Background facts flow automatically.

37sections in a drug monograph
2,711concept taxonomy, 19 clusters
55deterministic adapters
17terminology code systems
5citation kinds, all resolvable
8natural-language harness families
7product surfaces, one backend
100%of claims carry a citation

Counted from the codebase, July 2026. We publish only numbers we can point at.

Our mission

To make evidence-based medicine the path of least resistance — augmenting clinical expertise, cutting cognitive overload, and keeping every answer accountable to a source.

Why now

Forces converging into one moment.

Knowledge explosion

Medical literature grows faster than any clinician can track unaided.

Models that reason

Foundation models finally handle the nuance real clinical questions demand.

Decision fatigue

Documentation and decision load sit at an all-time high across health systems.

Scalable education

The next generation of doctors needs adaptive, personalised learning at scale.

Accountability

AI in medicine without rigour is a liability. Citations and human review are the answer.

Global inequality

Evidence-grade tools stay locked inside elite institutions. That can change.

Roadmap

A staged build toward a medical operating layer.

Live

Cited encyclopedia + evidence agent

Atlas and clinic.atlas in production, corrective-RAG on the answer path.

Live

Hospital deployment

The Hinduja antimicrobial guide — an institution's own antibiogram, in clinicians' hands.

In build

Claim-native knowledge base

Atomic, structured claims as the unit of truth — each with its own evidence and supersession.

Next

Unified intelligence layer

One backbone across practice, education and research, opened to more institutions.

Trust & rigour

A quiet promise about
how we answer.

Medical AI without rigour is a liability. Every layer is built to be auditable, and to fail safe.

  • Every claim carries a citation you can open — no source, no sentence.
  • When there's no evidence, it says so, instead of guessing.
  • Hallucinated citations are stripped and the answer is flagged — not papered over.
  • Safety-critical claims wait for a clinician to sign off before they publish.
  • Only allowlisted, authoritative sources are citeable.
  • Self-hosted end to end — database, auth, storage and search on infrastructure you control.

Not a substitute for clinical judgment. Handle patient identifiers with care — don't paste them into prompts.

Built for Indian practice

Clinicians and engineers, building side by side.

NMC-verified access, ICMR guidelines as a first-class source, UPI billing, and a live hospital deployment in Mumbai. Not adapted for India — built here.

SL

Co-founder

Dr. Sahil Langde

CEO, Physician & Co-founder

A physician-founder shaping Evidenceo's clinical vision — bridging bedside medicine with an evidence-native infrastructure.

NM

Co-founder

Dr. Niladri Bhusan Mishra

CTO & Co-founder

Architecting the intelligence layer — the retrieval engine, data model, and agent runtime behind the product family.

Join the next generation of
medical intelligence.

Early access is opening for doctors, students, residents, researchers and institutions. Be among the first to shape it.

No spam. Evidenceo Healthcare LLP · Sangli, Maharashtra.