LazyFox creates semantic understanding across enterprise data, so humans and AI can ask questions and get grounded answers. No migration required.
Built for organizations where data already exists, but meaning doesn't.
The challenge
Enterprises spent billions on data platforms. Yet answering cross-system questions still requires people who "know where things live."
Meaning lives in documents, spreadsheets, Slack threads, and in people's heads. Unstructured data remains largely invisible.
As AI enters the enterprise, this gap becomes critical. Models can reason, but they can't operate without context.
The approach
LazyFox sits above your existing systems and creates a semantic intelligence layer across structured and unstructured data. Without moving or duplicating it.
This layer becomes the interface between your organization and AI. Where meaning, context, and permissions converge.
We don't replace your data stack. We make it intelligible.
"AI doesn't fail because models are weak. It fails because context is missing."
The shift
This is not analytics. It's organizational understanding.
Timing
Most enterprises already run on modern data infrastructure. What's missing is not storage or compute. It's semantic understanding.
As foundation models commoditize, the scarce resource shifts from tools to context.
LazyFox exists because the next decade of enterprise software depends on meaning, not movement.
Stay informed
We're building alongside a small group of forward-thinking organizations and investors. If you want occasional updates as this category takes shape, leave your email below.
No newsletters. No spam. Only meaningful updates.
Thank you. We'll be in touch.