.png)
Most agencies aren't short on data. They're short on data they can actually use.
The culprit is a two-system reality most public sector IT has lived with for decades: a data warehouse built for structured reporting and a data lake built for advanced analytics, maintained separately, reconciled manually, and increasingly at odds with each other. When leadership asks "Can we use AI to improve service delivery?" the honest answer is usually "not yet" and the divided stack is why.
The fix isn't another tool on top of the existing architecture. It's collapsing the architecture itself into one unified platform where analysts and data scientists work on the same live data, governance travels with the data automatically, and AI has a trustworthy foundation to actually build on.
As AI transparency legislation accelerates across states, that foundation isn't optional. Auditors and oversight bodies are asking questions that a divided stack simply can't answer.
👉 Read the full breakdown, including five questions to pressure-test your current architecture on the Trading Post
Navigating this in your organization? We'd be glad to think through it with you.