PromptWake vs Microsoft Purview AI Governance

If you are a Microsoft-centric organisation, evaluate Purview first — regardless of what you conclude about us. You may already be licensed for a meaningful part of what you are shopping for, and buying a second product to do a job you already own is the most common expensive mistake in this space.

That said, the two products are usually being compared because of a wording collision rather than an overlap. Both get described as 'monitoring AI usage'. They monitor it for different reasons and stop at different points.

Purview's question ends where ours begins

Purview is data governance: classify sensitive information, discover where AI is being used across the estate, apply DLP policy to what people paste into AI tools, and support retention and eDiscovery obligations. The unit of concern is data, and the decisive moment is the one where data might leave. It is enterprise-wide, it is policy-driven, and it can block.

PromptWake starts one moment later. We are not asking whether the prompt should have been sent; we assume it was, and we keep it — along with what the model answered and which lines of which files changed as a result. The unit of concern is a change to a codebase, and the decisive moment is months later, when someone asks how that code came to exist.

A DLP policy stops measuring the instant the prompt is sent. That instant is exactly where the engineering record starts.

Two questions that sound the same

• "Did a developer paste customer data into an AI tool?" — Purview. It can see it, classify it, alert on it and block it.
• "Which prompt produced the retry logic in the payment service, and what did it say about idempotency?" — us. Purview has no reason to model that and does not.
• "Which unapproved AI tools are people using?" — Purview, together with your network or CASB tooling.
• "How much of last quarter's shipped code was AI-written, by whom, and at what token cost?" — us.
• "A customer's security questionnaire asks how AI-generated code is reviewed and retained." — both, honestly: Purview covers the data-handling half, we cover the provenance half.

Where Purview is straightforwardly stronger

It is enterprise infrastructure and we are not pretending otherwise. It covers the entire organisation rather than engineering, it enforces policy rather than recording facts, it integrates with the identity, retention and legal-hold machinery a large company already runs, and if you have the licensing it may cost you nothing additional. For the question it answers, it is the serious answer.

Our coverage is narrower by design: engineering machines, AI coding tools, and the code that came out of them. We do not block anything, we do not classify your document estate, and we are not an eDiscovery system.

What we do that a governance platform structurally will not

Link the conversation to the diff. That connection is the entire product: not that a prompt was sent, but that this prompt produced these lines in this file on this branch. A governance platform has no reason to reach into a developer's local tool history and reconstruct that — it is not a data-loss question, and the artefacts live in per-tool formats on laptops rather than in the tenant.

It is also the reason the two rarely compete in a real evaluation. They are bought by different people, for different fears, out of different budgets. When they do collide, it is usually because someone asked one team to 'cover AI' and that team reached for the tool they already had.

How to sequence them

Start from the consequence you are trying to avoid. If the worst outcome is confidential data leaving through a chat window, start with Purview and get the licensing question answered first. If the worst outcome is an incident nobody can explain because the conversation that produced the code is gone — and, increasingly, a customer asking a question about AI-written code that nobody can answer — start here.