Coval (YC S24)Simulation and evaluation platform for testing AI voice and chat agents at scale.
Overview
Key features
- Large-scale conversation simulation
- Voice agent testing with realistic dialogue
- Custom evaluation metrics and scoring
- Regression tracking across agent versions
- Scenario and edge-case generation
- Production traffic replay
Pricing
- Model
- Free
- Category
- Observability
- Rating
- 4.3 / 5 (4)
Use cases
simulate and stress-test voice AI agents
run thousands of realistic conversations before launch to identify potential failures and improve agent accuracy with 217% improvement in 7 days
catch failures in production
score every production call in real time and surface regressions before customers find them with full visibility into agent performance
sharpen evaluations with AI + human review
smart sampling routes failures to human reviewers for feedback that retrains the AI judge, enabling continuous improvement
Pros & Cons
Pros
- Purpose-built for agent testing rather than generic LLM evals
- Supports both voice and chat agent simulations
- Helps catch regressions across agent versions
- Customizable scoring metrics and scenarios
Cons
- Early-stage product still maturing
- Primarily aimed at technical teams and developers
- Pricing not transparently published
Reviews
Average from 4 ratings.
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Solid for our team
We rolled this out across the team last quarter and purpose-built for agent testing rather than generic LLM evals. Regression tracking across agent versions fits neatly into how we already work, and custom evaluation metrics and scoring removed a step we used to do by hand. but it has held up under daily use.
Compared a few options
Evaluated this against two competitors. Where it wins: custom evaluation metrics and scoring and customizable scoring metrics and scenarios. Where it lags: early-stage product still maturing. On balance the feature set — especially production traffic replay — justifies the 4 stars for our use case.
Does the job
Pretty happy overall. Production traffic replay just works and customizable scoring metrics and scenarios. Primarily aimed at technical teams and developers can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.
Years in this space
I've evaluated a lot of these over the years. What stands out here is regression tracking across agent versions — handled better than most — and supports both voice and chat agent simulations. Early-stage product still maturing is my one real gripe. Worth the time if this is your use case.
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