Evalgent — Voice Agent Evaluation & Testing Platform
Voice agent evaluation platform for AI teams. Test functional behavior, edge cases, and performance limits before your voice AI goes live.
Problems teams face without an evaluation layer
- Voice agents work in demos but break with real users — Demos don't reflect real behavior. Without a structured evaluation layer, teams lack a way to validate agents across scenarios and human interaction patterns before deployment.
- Teams can't tell if failures are edge cases or systemic — Without repeatable evaluation, teams can't distinguish one-off failures from underlying reliability issues.
- There's no visibility into how much user behavior agents can tolerate — In the absence of behavioral limit testing, deployment decisions rely on intuition rather than defined failure boundaries.
- Fixing one issue often breaks something else — Without a consistent re-evaluation framework, regressions go undetected across agent iterations.
How Evalgent solves these problems
- Scenario-driven functional evaluation — We define success at the scenario level and test whether the agent actually completes the intended objective end-to-end.
- Behavioral testing with human interaction profiles — We stress agents using real human behavior patterns instead of ideal users.
- Limit testing to define failure boundaries — We push behavior and conditions until reliability drops below acceptable thresholds.
- Statistical reliability measurement — Every test is run multiple times to measure consistency, not luck.
- Evidence-backed outcomes — Every success or failure is explainable and auditable.
How it works
- Define — Lock real scenarios and success criteria.
- Run — Run them under realistic human behavior.
- Measure — See what works, what fails, and where limits lie.
- Act — Get clear, actionable insights on what to fix, tune, or deploy.
What Evalgent is — and what it is not
| What It Is Not | What It Is |
|---|
| Post-hoc analysis on production transcripts | A pre-deployment testing layer that surfaces failures before users do |
| LLM-as-judge scoring alone | A controlled execution framework with defined scenarios and behaviors |
| Optional or "nice to have" | Foundational infrastructure for shipping reliable voice agents |
| A reporting or monitoring tool | A decision layer that determines production readiness |