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AI Evaluations & Testing

Prove an agent is right before a customer finds out it is wrong. Run it against eval suites and golden datasets in a safe sandbox, score the output, catch regressions on every change and red-team for failures — then gate the release on the result.

AI Intelligence Layer

Overview

An agent that handles three examples can still fail on the fourth. Evaluation is how you prove it works across the cases that matter — not just the ones you happened to try by hand.

Build eval suites from golden datasets, run agents in a safe sandbox on test data, score every output, re-check for regressions on each change, and red-team for the ways an agent could be pushed off the rails — all before it ships.

Explore AI Intelligence Layer →
  • ✓ Eval suites & scorecards
  • ✓ Golden datasets of correct answers
  • ✓ Safe test sandbox on sample data
  • ✓ Regression checks on every change
  • ✓ Red-teaming for unsafe outputs
  • ✓ A ship gate on the results
Capabilities

How you test agents

Eval suites

Score an agent against a suite of cases automatically, instead of spot-checking by hand.

Golden datasets

Curated sets of the right answers to measure accuracy and completeness against.

Sandbox runs

Run agents safely on test data, with no writes to production records.

Regression checks

Every change re-runs the suite, so a fix in one place never quietly breaks another.

Red-teaming

Probe deliberately for failures, jailbreaks and unsafe or off-policy outputs.

Ship gate

Only agents that clear the bar you set are allowed to go live.

What you measure

The dimensions a score rolls up

A single pass or fail hides too much. Evaluations score each output across the things that actually matter.

Accuracy

Does the answer match the golden result for the case, field by field?

Groundedness

Is the answer supported by your records, with a source, or invented?

Safety

Does it stay within policy and refuse what it should refuse?

Permission adherence

Does it touch only the data the user is allowed to see?

Latency

Does the run finish inside the time the workflow can tolerate?

Cost

Does it use the right model tier for the task, not an expensive one by reflex?

How it works

Live in four steps

1

Build the suite

Curate golden cases and the scorecards they grade against.

2

Run in sandbox

Test the agent safely on the cases, with no production writes.

3

Score & red-team

Grade every output, catch regressions and probe for failures.

4

Ship on pass

Only agents that clear the bar are promoted to live.

AI at work

How evaluation runs on the agent

Evaluations run each agent against your test cases, score the results and block release until it passes.

Sense

Reads the agent under test and the eval cases it must handle.

Decide

Scores each output and flags regressions and failures against the bar.

Act

Gates the release on the result — and the whole run is logged.

Five-tier model routing · field-level permissions · full audit trail. See the AI layer →

Use cases

Where teams put it to work

Confident launches

Ship an agent knowing it cleared the bar on the cases you care about.

Safe changes

Every prompt or tool tweak is regression-tested before it reaches production.

Safety assurance

Red-team for jailbreaks and unsafe outputs in testing, not in front of a customer.

Why it matters

The payoff

Confident releases

Agents go live only after they pass, not on a hunch.

Fewer surprises

Regressions are caught on every change, before anyone feels them.

Safer outputs

Unsafe answers are found in testing, not reported by a customer.

FAQ

Questions, answered

A set of cases with expected answers that an agent is scored against automatically, every time it changes.

Curated sets of correct answers you measure accuracy and completeness against.

It runs agents safely on test data with no writes to production, so you can test freely.

Deliberately probing an agent for failures, jailbreaks and unsafe or off-policy outputs.

Yes. Only agents that clear the evaluation bar you set are promoted to live.

Evaluation proves quality before release; Observability watches it continuously once live.

Ship agents you have actually tested

Start free, or get a guided walkthrough with our team — on the one platform that runs the AI Intelligence Layer and your whole business.