AgentGrade
Grade your AI agents' outputs objectively
AgentGrade scores AI agent outputs for quality, faithfulness, and task success, so you catch regressions before users do. You plug in trajectories and get comparable scores. It starts at $29/month.
AgentGrade scores AI agent outputs for quality, faithfulness, and task success, so you catch regressions before users do. Plug in trajectories, get comparable scores.
What it tracks
- Quality score
- Faithfulness check
- Task-success rate
- Regression tracking
The numbers behind it
- Starts at $29/month
- Scores quality, faithfulness, and task success
- Regression tracking across versions
What does AgentGrade actually score?
It scores each output for overall quality, faithfulness (does it stay grounded or hallucinate), and task-success rate, so a single number is not hiding a faithfulness problem.
How does regression tracking work?
It keeps comparable scores across versions, so when a prompt edit drops quality, you see it immediately instead of learning from a support ticket.
Do I need to hand-label data?
You feed agent trajectories; AgentGrade scores them without you labeling every output by hand, which is what makes weekly checks sustainable.
Who should run it?
Agent builders who ship often and cannot eyeball every run. It fits teams that treat prompt quality like code quality — measured, not assumed.
Where AgentGrade stops being useful
What AgentGrade does is narrow: Grade your AI agents' outputs objectively. It watches or grades agents, but a dashboard is not a kill switch. Keep a human accountable for what the agent actually does.
Accuracy and data questions
What does AgentGrade do?
AgentGrade scores AI agent outputs for quality, faithfulness, and task success, so you catch regressions before users do. You plug in trajectories and get comparable scores across versions.
How much does AgentGrade cost?
Plans start at $29/month (billed $290/year). Open the live tool for the current plan before adding it to your pipeline.
Who is AgentGrade for?
teams shipping or operating AI agents reach for AgentGrade when the job is: Grade your AI agents' outputs objectively.
What does the faithfulness check catch?
It flags outputs that drift from the source or invent facts, so a confident-but-wrong answer is scored down rather than shipped.
Do I need labeled training data?
No. You provide agent trajectories and AgentGrade scores them, so you get regression signals without hand-labeling a dataset.
How does it catch prompt regressions?
It stores comparable scores per version; when a prompt change lowers quality or faithfulness, the drop shows up on the next evaluation run.
How fresh is AgentGrade's data?
Not a travel agent or a safety authority. Verify bookings, visa, and local conditions yourself before relying on any plan.
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