The blocking point for AI projects in enterprises
Organizations aren't short of AI use cases. They stumble on a prior question: what data is the agent answering from, and who guarantees that data?
An assistant connected to ungoverned extracts produces plausible but indefensible answers. In an executive committee, a figure nobody can source is worth less than no figure at all.
What Partnership Brings
Dust brings the agent layer: building business assistants, connecting to workplace tools, distributing them at scale across the enterprise. dFakto brings, with beVault, the governed data foundation these agents rely on.
The combination answers the one question that matters to a CDO: how to deploy AI without degrading the reliability of information circulated internally.
- A historical Data Vault foundation, with source traceability for every value.
- An explicit semantic layer: business definitions are shared between humans and agents.
- Quality controls applied upstream, before exposure to agents.
- API exposure, designed for scripts, CI/CD, and AI agents.
Specifically, for data teams
No platform duplication: agents consume the same definitions and the same marts as reporting tools. A business rule is changed once.
No governance gray area either: rights, traceability, and history remain owned by the foundation, not delegated to the conversational layer.
Where to start
The fastest deployments start from a business scope that's already modeled and a question whose answer is currently costly to produce manually. Value shows up in weeks, not quarters.
Our teams scope this together with you, then build the tooling to make data available to agents via the beVault API.