Standardized onboarding
New clinicians ramp on the same vetted cases, so every hire starts from a consistent, certifiable baseline instead of whatever walks through the door.
ChatGeneT runs realistic, multi-turn consultations so junior clinicians can practice the hardest part of medicine: asking the right questions. Patients that lead with their worries, open up unevenly, and stay true to their history, available on demand.
Each session is a full multi-turn encounter. The simulated patient leads with what worries it most, volunteers history unevenly, asks its own questions, and sometimes holds back, exactly the way a real person does in the room. It is a safe place to build judgment before a clinician ever sits across from a patient.
New clinicians ramp on the same vetted cases, so every hire starts from a consistent, certifiable baseline instead of whatever walks through the door.
Objective, repeatable evaluation across the same scenarios turns informal judgment into a measurable, defensible signal of readiness.
Lifelike practice sharpens history-taking and reasoning, raising the quality and efficiency of real consultations once clinicians are on the floor.
Behind each patient response, ChatGeneT maintains a live representation of the case: symptoms, history, emotional cues, disclosed information, and unanswered clinical questions. This allows the simulator to adapt to the doctor's inquiry strategy while preserving realism and case consistency from start to finish.
Before the session starts, the agent loads the case record and builds a behavioral profile: what to present upfront, what to withhold, and how to respond under clinical pressure.
On every clinician message, the agent reasons about the patient's current emotional state, what has been disclosed, and what a real patient in this moment would plausibly say next.
Every disclosed fact, hesitation, and emotional beat is tracked in a session state. The patient cannot contradict what it said earlier, across a full 25-turn consultation.
When the session closes, the agent analyzes diagnostic coverage, question sequencing, and missed clinical leads to generate structured feedback for the clinician.
Most simulators send a single prompt and hope the model stays in character. ChatGeneT runs a multi-component agent loop — every response is planned, grounded against the case record, and verified before the patient speaks.
Maintains a structured log of every fact disclosed, every hesitation surfaced, and every emotional signal. The patient cannot contradict itself across a full 25-turn consultation.
Receives the clinician’s message and the full session state, then plans the patient’s next move: what to reveal, what to withhold, and how to frame the response authentically.
Grounds every generated response against the original case record before delivery. This grounding pass is what keeps hallucination below 0.31% across all sessions.
Runs post-session analysis on the clinician’s full query history: diagnostic coverage, question efficiency, and clinical leads that were missed or pursued too late.
Most medical AI is judged on the diagnosis. Our work focuses on the step before it: the questions. What we found reshapes how clinicians should be trained and assessed.
Inquiry quality sets the ceiling. A clinician with excellent diagnostic instinct still fails when the questioning is poor, and sharp questioning is wasted on weak reasoning. The weaker of the two decides the outcome.
Accuracy climbs as a clinician asks more, but only up to the point a real patient will stay engaged. Beyond that, people disengage.
Opening the encounter and surfacing the main concern the patient came in with.
Pinning down the character, timing, and severity of what the patient has already raised.
Probing related signs that widen or narrow the differential before committing.
Drawing out background and risk factors that can shift the diagnosis entirely.
Where a clinician spends their questions, across these four types, measurably changes the diagnosis they reach. ChatGeneT makes that skill practiceable and measurable.
Share of replies that contradict the patient’s own record. Lower is better, and ours sits far below earlier systems.
How human the patient feels: emotion, initiative, and natural phrasing, scored from 0 to 1.
Real patients sometimes sidestep a question. We preserve that instead of forcing tidy answers, so practice matches the clinic.
High satisfaction from clinicians training on the simulator.
Standardized onboarding and assessment at scale.
Deployed for onboarding and assessment across partner sites.
Real consultation behavior distilled into the training corpus.
“Realistic multi-turn patient dialogue gave our junior clinicians a consistent way to practice and be assessed, training and assisted consultation finally on the same standard.”
We work with hospitals to roll out ChatGeneT for onboarding and competency assessment. Reach out to see the simulator in action.