Agent Training Simulators
AI that role-plays the difficult customer so your agents practise on realistic calls — then scores the conversation afterwards.
6–10 weeksCapability — no named deployment published
The inversion of a normal voice agent: here the human is the agent and the AI is the customer, often irate, accented or talking over them. Trainees take live practice calls against configurable personas and receive a scored performance report afterwards, so training happens against realistic pressure rather than a colleague reading a script.
What this solves
- New agents learning on real customers
- Role-play practice depending on trainer availability
- No objective measure of whether a trainee is ready
- Difficult-customer scenarios being the ones least practised
What you get
- Configurable customer personas — irate, confused, accented, language-dominant
- Full-duplex conversation where the AI can interrupt the trainee
- Browser-based practice calls over WebRTC
- Timestamped transcript of every session
- Automated scoring and a structured performance report
Technology
PipecatWebRTCSarvam AIOpenAIFastAPI
Industries
Talk to the engineers who build it
Tell us the problem and we'll tell you whether agent training simulators is the right answer — and what it would take.