Built by engineers who've lived the problem

"The problem of specification quality isn't new. What's been missing is the ability to turn real-world experience with requirement pitfalls, delays, and cost impacts into a structured, repeatable analysis engine. That gap is what Wyzer Detective addresses."

We built Wyzer Detective because we've seen firsthand how requirements issues translate into delays, cost overruns, and integration problems at scale. The Sherlock engine is built on lessons learned in practice — turning the kind of expertise that comes from decades on real programmes into a consistent, automated process available to every engineering team.

The approach combines AI-driven analysis with deterministic rule-based validation, so findings are not only comprehensive but also consistent, reproducible, and explainable. That combination matters: a quality gate that produces different results run to run is not a quality gate.

Specification quality is a solvable problem. Describing it as a process failure or a skills gap misses the structural reality: the volume and cross-team authorship of modern engineering specifications exceeds what sequential human review can reliably cover. A thousand-requirement document with multi-team authorship creates more pairwise relationships than any review board can hold in working memory. Systematic analysis changes that.

Before building Wyzer Detective, both founders spent years inside the programmes where specification errors became rework, delays, and integration failures. These posts are written from that experience.