No. ActionProof drives synthetic conversations against a development, staging or dedicated test environment. Production monitoring is a separate capability that is coming later.

Model-based judging only grades the text. We additionally verify tool calls, their arguments and the resulting business outcome deterministically, so an agent cannot pass by sounding confident.

Yes. Any agent reachable over HTTP works — LangChain, LangGraph, CrewAI, vendor platforms or a fully custom stack. You map the request and response fields once during setup.

They are generated from your policies, knowledge base, supported workflows and past failures, then reviewed and edited by your team. You can also write scenarios manually or import them.

Scenarios use synthetic customers and synthetic records by default. Test runs point at sandboxed tools and APIs, so no real refunds, cancellations or account changes occur.

Yes. Trigger suites from GitHub Actions or any CI system, gate releases on critical regression tests and receive results via webhook or Slack.

Voice testing is in development and uses the same evaluation layers, adding transcription accuracy, interruption handling and latency measurement.