No longer a “tool” or “platform”.
Maia is the data team that runs in your architecture.

What changes when AI moves from assistance to autonomous execution. Watch Maia plan structured work, apply your team's patterns through Skills, and ask for business context before it builds — the Reverse Prompt that separates a context-aware data team from generic AI. The starting point for every other capability in this launch.

Mission Control intercepts a null-value spike in a Lead_Score field before a single bad row reaches a marketing dashboard. Because Context Engine understands how that field is used downstream, Maia doesn't surface a raw error code — it pauses the pipeline, opens a ticket, and proposes the exact transformation logic to fix it. The Data Manager reviews, clicks Approve, Maia implements. Governed autonomy in production.

Hand Maia the internal API documentation for a tool with no off-the-shelf connector. Guided by Context Engine, Maia generates a fully functional connector and a business-specific test framework — tests written against your actual schemas, naming conventions, and regional compliance requirements. Days of Python scripting become minutes of supervision. Output is production-ready from the start.

Mission Control is how a Data Manager runs the whole estate from a single view. Every migration, pipeline builds, quality fix, and Reverse ETL job ands on one Kanban board with the same flow. Maia plans the work, surfaces it for approval, executes, and reports back. Maia handles execution and your team handles decision-making.