AI patients who react like real people, an AI supervisor that explains every score, and cases that carry on from one session to the next.
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Over 120 simulated patients, each with their own history, mood and trust in you. They open up gradually as rapport builds, and pull back if a question lands badly.
Run sessions in CBT, REBT or SFBT. Each session is checked against the competencies expected at that phase of therapy.
An AI supervisor scores the session, explains each score, and points out missed opportunities with other ways you could have responded.
The same patient remembers earlier sessions, so you can work a case over several meetings instead of starting from scratch each time.
Speak to the patient and hear them answer, so the practice feels closer to a real room than a chat window.
Faculty and supervisors follow each trainee's sessions, scores and growth over time, and can review the AI's feedback themselves.
From mild to severe presentations, including situations common in Indian practice. Each persona has its own history, speech style and beliefs, and no two patients built from it tell their story the same way.
Create a training patient and a persona is assigned at random from those that fit the patient's gender, age group and marital status, so trainees can't prepare for the case in advance.
Pick any persona yourself, then shape it: the case story, how open the patient is, how intense their emotions run, how they speak, the painful memory they guard and what makes them cry, and the beliefs behind their thinking.
Choose a persona yourself or let the system assign one, then pick the approach you want to practise: CBT, REBT or SFBT.
Talk or type. The patient responds to what you say, and trust builds or drops as the session goes.
See your scores with the reasons behind them, what you missed, and other responses you could have tried.
The patient remembers. Pick the case up where you left it and see whether you're improving.
Hours of realistic practice before placements, without risk to a real patient.
Give a whole cohort consistent practice cases, and let faculty follow each student's progress.
Train new clinicians and interns on the same platform they'll later use with real patients.
From training to practice
Trainees practise on AI patients with feedback after every session. Once they see real patients on the same platform, supervisors can review their notes, discuss cases with them, and keep an eye on high-risk patients, without anyone switching tools.
Running a practice too? See the practice tools
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