"Ask Medows" is the consult button on every patient card. It looks like a search box. It is not a search box.

The architecture behind it is what makes it different from typing the case into ChatGPT or UpToDate or OpenEvidence. Three components:

Context retrieval. When the doctor opens the AI consult, the patient's current state — vitals, recent labs, completed tasks, active medications, demographics, the last twelve hours of trend data — is automatically retrieved and embedded into the conversation. The AI does not see the doctor's question alone. It sees the question and the patient.

Source-grounded generation. The AI's response is generated with reference to a structured corpus of clinical guidelines — AIIMS clinical protocols, ICMR documents, NICE guidance, drug references. Every claim in the response is attributable to a source. The citations are inline, with chip-style references the doctor can tap to see the underlying document.

The interface lives in the patient's surface. The consult is not a separate tab. It is a panel that opens within the patient's card, with the patient's vitals visible above the conversation. The doctor doesn't switch context. The AI doesn't lose context.

The combination is what we mean by "context-aware AI." Not "an AI that knows everything," which is impossible and unhelpful. "An AI that knows this patient," which is achievable and useful.

The published frameworks for this — retrieval-augmented generation, RAG, grounding via document retrieval — have been mature for a couple of years now. What's new in Medows is the clinical-workflow layer. The doctor doesn't think about retrieval. They think about the patient. The retrieval happens because the patient's card is the starting point of the conversation.

Three things "Ask Medows" is not:

Not a diagnosis tool. The output is decision support, not a decision.
Not a substitute for the senior consultant. The output sits next to the patient context it used, so the consultant can verify.
Not a clinical search engine. The starting point is the patient, not the question.

The point of the architecture is to remove the cognitive overhead of asking the question. Restate the case. Look up the guideline. Verify the dose. Check the interaction. Five steps become one — for the AI part. The doctor's clinical judgment is still the doctor's clinical judgment.