AI Agent Evaluation

Validate AI Agents for accuracy, consistency, and production-readiness

[SEE A DEMO](/content/cs/c/?cta_guid=9ef76d81-e418-4f28-8d3b-dfecae771b62&signature=AAH58kG4aQPfrjvf-HpTUw8r16OxyshkNg&portal_id=2761836&pageId=206963684921&placement_guid=94f84835-3209-4450-ad4d-7426a78cbc39&click=08631247-3cba-454b-8df6-4d0ca341cd7f&redirect_url=APefjpEEbhBNeUXzg9NHMul07CpCyKdRVaP3PHwEycqTXa2zNXHNL4KNrA1vXoUmmKPaFcnptCPCJJ3PTdhW-mtnOK7A_CHbsNVHUEQTEtLV4yIxjEcT08m6xHH8x7g6q5cTAdw3A2Wv&hsutk=&canon=https%3A%2F%2Fwww.cognigy.com%2Fplatform%2Fai-agent-evaluation&ts=1784306999789 "SEE A DEMO"/index.html)

Simulator lets you stress-test AI Agents across thousands of realistic conversations. Measure performance against explicit success criteria, compare variants, and deliver consistent outcomes in production.

Prove Your AI Agents Before Customers Do

More AI Agents are going live, but fewer teams can clearly show how they’ll perform. Simulator lets you run large-scale evaluations to assess how Agents behave under pressure at scale, before they go live.

Use data, not assumptions, to prove AI Agents are ready for real-world complexity.

Confidence Before Deployment

Stress test behavior across happy paths, edge cases, and failure scenarios, and ship only when performance meets your standards.

Faster Iteration Without Risk

Replace slow, manual QA with automated evaluations, instant scoring, and actionable insights that accelerate release cycles.

Enterprise-Grade Reliability at Scale

Maintain consistent performance as Agents evolve, flows change, integrations update, and foundation models shift.

Continuous Evaluation for Agentic AI

Mirror Real Customer Behavior

Define test scenarios using synthetic customers that reproduce real language patterns, intents, and behavioral edge cases. Each scenario pairs a persona, a mission, and success criteria so results are measurable, not subjective.

Tailor your own scenarios or generate them automatically using existing AI Agents and real-world transcripts.

Run Evaluations at Scale

Execute simulations on demand, on a schedule, or as part of automated regression testing. Run broad sets of conversations that introduce natural variations, quickly revealing the rare behaviors that only surface through extensive, automated testing.

Model Real-World Dependencies

AI Agents rely on APIs and backend systems where varying response paths intensify complexity. Timeouts, server failures, authentication issues, and alternate success paths.

Simulator lets you mock the full range of third-party responses across success, degradation, and error states, exposing how Agents respond without depending on live environments. This hardens mission-critical integrations and reduces risk in production.

Score, Compare, and Improve

Automatically score results against configurable criteria to immediately assess agent performance. Drill into failed conversations to identify friction and pinpoint exactly what needs to change.

Monitor success rate over time to detect regressions early and validate performance after updates.

What Simulator Proves

Task Success & Goal Completion Did the AI Agent resolve the customer’s mission?

Guardrail & Policy Adherence Did the AI Agent stay within compliance and safety boundaries?

Integration & Tool Performance Did API calls, workflows, and back‑end processes behave as expected, even in adverse conditions?

Experience Quality Was the conversation clear, helpful, and on‑brand?

Multilingual Consistency Did performance hold up across languages, regions, and customer segments?

See Simulator in Action at Our Launch Webinar

From Testing to Continuous Evaluation

Deploy AI-driven CX with confidence, speed, and agility