the proving ground
You shipped agents, or someone did, and now they answer customers, touch real systems, make real calls. Where do they hallucinate? Where did the last prompt change quietly break them? We find out before your customers do.
what the proving ground is
Most teams ship an agent, watch a few demos go well, and call it done. Then a model update lands, a prompt gets tweaked, and it starts failing silently in front of real people. No test suite catches it because there is no test suite.
We build one. Eval sets from your real traffic, adversarial tests that try to break the agent on purpose, and a reliability score you can actually trust. We did not have to build your agent to prove it. We just have to be able to run it.
what we catch
We build cases where the agent is tempted to invent a policy, a price, or a fact it does not have. The ones it makes up land as failures with the exact prompt that triggered them, not a vague warning.
Every model swap and prompt edit gets re-run against the full suite. When v7 breaks the refund flow that v6 handled fine, you hear it from us, not from an angry customer.
We test the calls your agent actually makes: wrong arguments, the tool skipped when it was needed, the tool fired when it should not have. The failures that cost money because something real happened.
We run prompt-injection and adversarial attacks against it: instructions hidden in inputs, attempts to leak your system prompt, requests to do things it should refuse. You see exactly where it caves.
Empty fields, wrong languages, hostile phrasing, the long messy request nobody scripted. We map where your agent has no coverage, then build the cases that live there.
An agent that scored 94% in March and 81% today did not fail loudly. It drifted. We track the score over time so the slide shows up as a line, not a surprise.
how it runs
01
We sit with your agent and its real traffic to pin down every job it does and what a correct answer looks like for each. You cannot grade an agent until everyone agrees what passing means.
02
Eval cases from your real conversations, plus adversarial and safety tests we write to break it on purpose. We run the first pass and hand you a reliability score with every failing case attached.
03
The suite runs on a schedule and on every prompt or model change. When something breaks or drifts, you get the failing cases and the score movement, before it reaches a customer.
No. The Proving Ground is for whatever you are already running in production, wherever it came from. Your team built it, an agency built it, a framework built it, does not matter. If we can run it, we can prove it.
Eyeballing catches the failure you happen to scroll past. A suite catches the one at 2am on an input you never imagined, and it catches the regression the moment a prompt change ships. You get a number that moves, not a gut feeling.
Ongoing eval and QA runs as a retainer from $5,000/month, because catching failures is a thing you do continuously, not once. See the full ladder at /pricing. You get the exact number in writing after the free audit, before you spend anything.
A way to run the agent and a slice of your real traffic to build cases from. Least-privilege access, every run logged, and we sign an NDA before we look at anything sensitive. Your data stays in your systems.
The free audit runs a first look at one live agent and shows you where it is quietly failing. All before you spend a dollar.
We take on companies ready to invest $5,000+/month in doing this properly.
