Agent Evaluation and Benchmarking Platform
A platform for systematically evaluating AI agent performance against custom test suites.
- Target market
- AI engineering teams, QA teams at AI-first companies, product managers overseeing AI features, MLOps engineers
Problem snapshot
What this solves
There's no CI/CD for AI agents. Teams push agent changes to production and pray. When they update prompts, swap models, or change tool configurations, they have no systematic way to know if the agent got better or worse.
Full ProvenTools analysis
Unlock the full analysis and build prompt
Unlock the solution, revenue model, feature scope, technical approach, user flow, and 13-section AI build prompt.
Already have access? Sign in
Related ideas
Explore similar problems
Agent Canary Task Monitor
Runs a handful of known-good canary tasks against your live agent on a schedule and alerts the moment its output, tool path, latency, or cost drifts from baseline.
Agent Context Drift Alarm
Scans the assembled context (retrieved chunks, memory, task) for contradictions and topic mismatch before the agent answers, so it clarifies or prefers the authoritative source instead of confidently resolving a confl...
Agent Failure Packet Recorder
Captures a single self-contained, redacted bug packet only when an agent run fails, so a vague complaint becomes a reproducible case without recording every healthy run.