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JamEMR

Features

AI Assistant

A chart-aware assistant that summarizes the record and answers questions grounded in this patient's actual data — with the clinician always in the loop.

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Ask the chart a question

Before a visit, a clinician needs the story: what has happened since the last encounter, what is outstanding, what changed. JamEMR’s AI Assistant reads the chart so the clinician can ask instead of dig — “summarize the last three visits,” “what were the most recent renal results,” “is there a documented allergy history?”

Answers are grounded in this patient’s actual record. The assistant is not a general chatbot with medical opinions; it is a reading tool for the chart in front of you, and it shows its work.

The AI Assistant is in pilot validation with practices using JamEMR today.

What it does

  • Pre-visit summaries. A concise brief of recent encounters, results, and open items, generated on demand.
  • Grounded question answering. Ask about the record in plain language; answers cite the notes, results, and documents they came from.
  • Chart navigation. Answers link back to their sources, so verifying takes one click, not a search.

Grounded, cited, and reviewed

The failure mode of clinical AI is confident fabrication. The assistant is built against it:

  • Answers come from the record. The assistant retrieves from this patient’s chart and the structured Clinical Knowledge layer, not from general model memory.
  • Every claim carries its source. If the assistant says a result was abnormal, it points to the result. If it cannot find support in the chart, it says so.
  • Nothing is written without review. The assistant informs clinical judgment; it does not substitute for it. It does not place orders, alter the record, or make care decisions.

Your AI, on your hardware

The assistant’s inference runs on the practice’s own dedicated local GPU hardware. Questions about a patient — and the chart data used to answer them — are not sent to third-party consumer AI clouds. That is not a configuration option bolted on afterward; it is the architecture JamEMR was built on, and it is why a practice can offer chart-aware AI to its clinicians without renegotiating where protected health information travels.

For clinicians, the result is simple: the time between “I need to know” and “now I know” shrinks from minutes of tab-hopping to a sentence and a glance at the sources.

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See JamEMR in action

Join the pilot program or request a live demonstration for your clinic.

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