Less rework. Fewer surprises. Better sign-offs.
Five views into the same document.
Wyzer runs five analyses on every document — then gives you the tools to act on what it finds. Score each requirement for quality, spot contradictions before they become contract disputes, find what was never written down, check every clause against the standards you have to meet, and explore the full web of dependencies.
The system shall respond quickly to user input under expected load conditions.
The system shall respond to user input within 200 ms (P99) when sustaining ≤ 500 concurrent sessions, as defined in §3.2 Load Profile.
Five business risks every specification carries.
Rework costs more than the fix.
Finding a conflict after build has started costs 29× more than catching it before sign-off. Change requests negotiated under delivery pressure rarely go in your favour.
Programme slippage starts in the spec.
Most schedule overruns trace back to ambiguous or missing requirements that nobody questioned at the start. Every week lost to late-stage rework is a week that was already visible in the document.
Specification gaps erode contract margin.
Suppliers price for what is written. Gaps become change requests. Change requests become margin loss. Wyzer surfaces what is missing before the contract is signed — while there is still time to protect the number.
Missing compliance becomes an audit failure.
New rules and standards do not pause your programme. Wyzer checks your specification against the obligations you are contractually or legally bound by — before you submit, not after the audit flags the gap.
Recalls are traceable to documents.
93 million vehicles were recalled across 2023–2025. Most failures were present in the requirements document long before a single part was built. Customers and regulators do not distinguish between engineering error and business failure.
The tools that turn findings into action.
Sherlock is not a general-purpose AI — it is a purpose-built engine trained specifically to interpret engineering requirements at scale. It pairs AI-driven semantic analysis with deterministic rule-based validation, so every finding is consistent, reproducible, and explainable.