Built with agentic AI, proven before we pitch it
Directory Hygiene isn't a mockup commissioned to illustrate a pitch. It's a real product, built end-to-end with agentic AI under the same review discipline described below, not a slide deck about what AI can supposedly do. Here's exactly what that looked like, and what it changes for your own engagement.
What we actually built this way
Directory Hygiene, our review-gated Active Directory and Entra ID remediation tool, was built session by session with an AI coding agent doing the implementation, under our own direction and review at every step, not a one-shot generated product we shipped unchecked. The same discipline that makes the product itself trustworthy (nothing writes back to a directory without a human sign-off, see Directory Hygiene) was applied to building it: every change reviewed, tested, and signed off before it shipped.
You can see the real product, not a description of it, in the demo: actual screens against a real dev tenant, the actual propose-and-sign-off flow, not staged screenshots.
The discipline behind it
Agentic AI makes it possible to build and iterate fast. That's exactly why the review discipline around it has to be real, not relaxed: speed without independent checking is how a subtle defect reaches production unnoticed. Every change goes through the same three-part cycle regardless of how quickly the AI agent produced it:
- The change is built and validated against the actual requirement, not assumed correct because it compiles
- An independent QA pass verifies the change itself, runs a full regression check, and confirms nothing else on the platform was affected
- A second, separate pass audits that QA review itself for completeness and accuracy, rather than trusting a single pass by default
- Every defect found is logged with its root cause and fix, so the same mistake gets caught structurally next time, not just patched once
This is how we build our own products. It's also newer ground than a decade of hands-on IAM delivery: as with any capability we're upfront about, we'll tell you plainly where our experience starts and stops.
What this means for your engagement
Where a client engagement involves building something (a remediation tool, an internal dashboard, a process automation, a piece of tooling your existing platform doesn't cover) rather than just configuring an off-the-shelf product, we can bring this same agentic-AI-driven approach to it: faster iteration on the actual working thing, checked by the same independent review discipline described above, not a faster route to something unreviewed. Where the engagement is advisory or architecture work, the same tooling speeds up the unglamorous parts (documentation, evidence packs, consistency checking across a large estate) without changing who's accountable for the judgment calls.
Looking to govern your own AI agents, not build with them?
Service accounts, API keys, and autonomous AI agents acting under delegated identity are a governance problem in their own right, separate from how any of us build software.