The niche: quality and safety testing for AI agents
Teams shipping agent updates regularly.
Why this niche exists now
- Model and prompt updates are frequent.
- AI-graded tests are inconsistent.
What people use today, and where it falls short
| What teams do today | Where it falls short |
|---|---|
| AI judges | Inconsistent. |
| Manual spot checks | Miss path changes. |
What makes AGENT-CI different
- No AI judge.
- Checks the path, not only the answer.
- Pinned suites.
How big is the opportunity?
Do not quote market-size statistics on a call. Most published figures are surveys or vendor estimates, and a smart buyer will ask for the source. Size the opportunity per prospect instead, with these questions:
- How often do you change your agent?
- How do you test it?
If the honest answers are "no" or "not yet", they are not a buyer today. Note it and move on; that is good selling, not failure.
Explain the niche in 30 seconds
Teams shipping agent updates regularly.
AGENT-CI tests a new version of an AI agent against the old one, case by case, on the answer and the path it took, with no AI judge.
Practise saying this out loud until you can do it without reading. Then say it in your own words.
Words your buyers use
These are the phrases people in this niche type into search engines and use in posts and job ads. Use them to find prospects (page 3) and to talk their language:
agent evaluation LLM regression testing agent evals LLM-as-a-judge problems
Sell it together with
Buyers rarely have just one problem. When this product fits, these often fit too:
| Product | Why it goes together |
|---|---|
| KEYSTONE CI | gate code changes |
| Swarm KEYSTONE | multi-agent structure |
| Deterministic math gates | sample sizes for agent tests |
Rule: open with one product. Mention a second only after the first is agreed.
Next: who buys and where to find them →
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