Comparisons
Most of the products PromptWake gets compared to are not competitors — they answer a different question about AI, and the overlap is in the vocabulary rather than the job. Each page below says what the other product does, where it is genuinely stronger, and when it is the one you should buy.
The one that actually competes
AI code provenance
LLM observability
Langfuse traces the LLM calls your application makes. PromptWake records the AI conversations your developers have. They are not alternatives — here is how to tell which one your question belongs to.
LangSmith traces the agents you build. PromptWake records the agents you use. Both talk about 'agent runs' — and that shared word is the reason these two end up in the same evaluation.
Helicone logs the model calls your application makes, usually by pointing your base URL at their proxy. PromptWake records the AI coding your developers do — which never passes through any proxy you control.
"We already have Datadog" is the most common reason teams skip this category. It is a good reason for the half Datadog covers, and it says nothing about the half it does not.
LLM gateway
Prompt management
AI evaluation
Data governance and DLP
Purview asks whether sensitive data left the company through an AI tool. PromptWake asks what AI built and whether you can reconstruct why. Two questions, two products — and if you are a Microsoft shop you may already own one of them.
Netskope can tell you which AI tools your people use and stop sensitive data reaching them. It cannot tell you what those tools wrote into your codebase — the traffic is encrypted to a vendor and the record is a file on a laptop.
Zscaler governs what reaches AI services from your organisation. PromptWake keeps what AI services sent back into your codebase. The first is a gate; the second is a ledger — and a gate keeps no ledger.
