AI agents can act.
But can they actually perform?
Expert evaluation for AI agents doing real work. We watch what your agent does, judge whether it holds up, and show you where it breaks.
Every evaluation, end to end.
We follow the whole trajectory — including the moment something goes wrong and how the agent recovers.
- Task receivedA real task from your domain
- PlanningThe agent decides how to approach it
- ExecutionIt writes, calls tools, and acts
- ProblemSomething doesn't go to plan
- RecoveryIt adapts — well or badly
- ResultThe agent reports what it did
- Expert reviewA person judges whether it holds up
What we assess
The agent executes. The expert evaluates.
Automated checks tell you whether the tests passed. They can't tell you whether passing the tests meant the job was done.
What actually works
Which tasks your agent handles reliably, and which only look handled.
Where it fails
The specific failure, the step it happened at, and why it wasn't caught.
Why it happened
An expert's diagnosis in plain language — not a score with no explanation.
What to fix first
Findings ordered by what would most improve real-world reliability.
Tool use
Whether the agent chose the right tool, and used it correctly.
Recovery quality
When something went wrong, whether the workaround was sound or just lucky.
How it runs
Scoped small enough to prove the value quickly.
Bring us a capability you're trying to measure. We design the task set, the rubric, and the reviewer pool around it.
Define the capability
We agree what the agent is supposed to be able to do, in concrete terms.
Build the task set
Real tasks from your domain, including the ones that are hard for the right reasons.
Qualify reviewers
Reviewers are assessed against the domain before they judge anything.
Review and report
Every trajectory is reviewed end to end, with findings ordered by impact.
Who does the work
Judgement needs someone who has done the work.
That judgement needs someone who has written, reviewed, and debugged the kind of system your agent is working on.
- Software engineers
- Systems engineers
- Security engineers
- ML practitioners
- Domain specialists
Know what your agent can actually do.
Bring us a capability you're trying to measure. We'll design the task set, the rubric, and the reviewer pool around it — scoped small enough to prove the value quickly.