Recorder AI

Recorder AI captures interaction data and prompts from AI-assisted workflows to create a reproducible record of sessions. It records event types such as 'prompt', 'action', and 'api_call', along with timestamps and payload metadata. This enables debugging, auditing, and iterative improvement of automation pipelines.
Conceptually, the tool normalizes diverse data streams into a structured log, masks sensitive fields when configured, and exports artifacts suitable for version control or CI integration. Users supply a capture scope and duration; the system streams events to a backend or local store and can generate a replay script for testing environments.
Beneficiaries include developers, QA teams, data scientists, and product managers who design AI prompts or chat flows. The unique value lies in combining multi-source capture with privacy controls and ready-to-replay artifacts, reducing debugging time and enabling reliable automation design.
Core features include: event-level logging with deterministic ordering, configurable field masking, export of JSON payloads, optional CSV summaries, and programmatic API access. Typical use cases are auditing prompt changes, documenting automation steps, and exporting logs for reproducibility.