A human evaluator and participant hold a live feedback session that is recorded and transcribed. No AI agent joins the room — analysis happens asynchronously after the session ends.
What this use case is
Feedback Evaluation records a human-to-human feedback session and analyzes it afterward. The evaluator runs a live session in a WebRTC room with live captions; there is no AI persona in the conversation. Once the session ends, the transcript is uploaded and the LLM runs a dual analysis — scoring the participant's performance and assessing the evaluator's feedback quality — then maps the results onto an evaluation form.
Interaction pipeline
The ordered path a session takes through the platform for this use case.
Architecture highlights
Platform capabilities
Explore the architecture
Infrastructure diagram, traffic flow, and key specs.
Standard Cloud, Hybrid, and Self-Hosted options.
Six-layer defense-in-depth controls.
Every phase, route, and protocol for this use case, end to end.