If you’re building an AI security product, you already know it needs to be right. The hard part is knowing where it’s most likely to go wrong, and what to do first.
In our experience, products usually get caught out in one of three places. Each has a different cause and a different fix.
1. Before a pilot: verdicts nobody outside the build team has checked
Your team has tested the product thoroughly, but always with the same assumptions it was built with. The first people to look at it with fresh eyes are a buyer’s analysts during a pilot. That’s the worst possible time to discover that some verdicts are right for the wrong reason, or that harmless activity is flagged at high severity.
Signs this is you: a big pilot or launch is coming up, and nobody outside your team has reviewed real outputs.
The fix: an expert evaluation. Independent practitioners use your product the way a customer’s team would, review every verdict, and tell you what to fix first.
2. Between releases: tests too clean to catch regressions
Your tests pass, but they run in an environment far tidier than any customer’s, often without known answers. Releases look fine internally, then customers report new false alarms or missed detections.
Signs this is you: you ship often, and you can’t say with numbers whether the last release was better or worse.
The fix: realistic evaluation infrastructure, with lived-in identity, cloud and endpoints, background noise, and a known answer for every test, so every release gets a score.
3. At customer sites: deployments never tuned to the environment
The product works in the demo, but each customer’s environment is different: their naming, their VPNs, their noisy tools, their critical systems. Without tuning, the verdicts don’t fit, and the customer’s team quietly stops using it.
Signs this is you: deployments take longer than planned, usage drops after the first month, or renewals feel uncertain.
The fix: Forward Deployed AI Security Engineers, who work inside each customer’s environment and tune your product with approved, scoped context.
Where to start
Most teams start with a short expert evaluation. It’s the quickest way to see how your product looks to a practitioner, and it usually shows where the other two would help most.
If you’re not sure which of the three applies to you, that’s a good conversation to have before a customer answers the question for you.