Agent Testing
Autonomous AI evaluators for chatbots, voice, image, & phone. Catch hallucinations, bias, & more.
🛡️ AgentReady threat assessment
MAESTRO 7-layer threat model + OWASP AIVSS risk score for Agent Testing, derived from its capabilities.
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology — every score is re-derived by the same automated method as an agent's public evidence changes.
Overview
Agent Testing deploys 15+ autonomous AI evaluators to validate chatbots, voice assistants, and phone agents before and after deployment. Upload your context, auto-generate 60–100 scenarios, and get a production-readiness verdict: Green, Yellow, or Red. Scores across 9 quality metrics, including hallucination, bias, toxicity, completeness, and context awareness. Covers chat, voice, phone inbound, phone outbound, and image agents. Catch failures before your users do.
Key features and capabilities
- 15+ autonomous AI evaluators run in parallel, each specialized in a distinct quality dimension
- 5 agent surfaces: chat, voice, phone inbound, phone outbound, and image
- 9 quality metrics (30+ for phone): hallucination, bias, toxicity, completeness, context awareness, and more
- Auto-generated scenarios: Upload a PRD, doc, or JIRA ticket to create 60–100+ tests instantly
- 10 persona types: Angry callers, confused customers, international speakers, and more
- 200+ voice profiles, 50+ accents, 15 noise presets for realistic voice testing
Use cases
- Pre-launch validation: Verify a new chatbot or voice agent is production-ready before go-live with a Green/Yellow/Red verdict.
- Regression testing: Confirm nothing broke after a model or prompt update by comparing scores to baseline.
- Production monitoring: Upload real call recordings to catch quality drift synthetic tests miss.
- Compliance audits: Generate auditable, reproducible evidence for regulatory documentation.
- Model comparison: Run identical suites on two variants and pick the better performer on data, not demos.