Agent test harnesses
Wrap any agent — API, browser, or CLI — in a harness that replays real transcripts and scores every step, not just the final answer.
See a sample harness
Now tracking 214 agent deployments
Know exactly when your agent stops working.
Building Evaluation Consulting builds the test harnesses, regression trackers, and reliability benchmarks that catch agent failures before your customers do.
12,400+
Eval cases run last week
38%
Average hallucination reduction
6
Reliability benchmarks maintained
4m 12s
Median full-suite run time
What we build
One reliability layer, six ways to use it
Each product ships as a standalone tool or as part of a full evaluation pipeline — connect what you need, skip what you don't.
Prompt-regression trackers
Catch the exact commit or prompt edit that made an eval score drop, with a diff view built for prompts instead of code.
See regression historyRed-team evals
Run adversarial prompts, jailbreak attempts, and edge-case user behavior against your agent before someone else does.
See attack coverageHallucination detectors
Flag ungrounded claims in code agents and support agents by checking output against the source they cited.
See detection accuracyLong-horizon reliability benchmarks
Measure how an agent's accuracy holds up across a 40-step task, not just a single-turn question.
See benchmark methodologyCost / latency / quality dashboards
See the three numbers that actually trade off against each other, per model version, in one place.
See a live dashboard
How it runs
From first connection to a trusted release gate
The pipeline runs in this order every time — each step depends on the one before it.
01
Connect a harness
Point us at your agent's API, repo, or transcript logs. Most teams are running their first eval within a day.
02
Define the eval suite
We turn your real support tickets, tasks, or codebase issues into scored, repeatable eval cases.
03
Run continuously
Every deploy, prompt edit, or model swap triggers a full run — no one has to remember to check.
04
Review and gate
Regressions block the release until a person signs off, with the exact diff that caused the drop.
Dashboards
Cost, latency, and quality — read together, not separately
A model that's 4% more accurate but 3x the cost isn't automatically the right call. See the trade-off before you make it.
Quality score, last 30 days
- agent_v3
- agent_v2
Latest run by model version
agent_v3
96.2%
agent_v2
88.4%
agent_v3-lite
91.8%
See your agent's reliability score
Send us your agent's docs or a sample transcript. We'll run a starter eval suite and send back a scored report — no setup required on your end.