AI in Superset

AI inside Apache Superset — implemented in your fork, on your terms.

Scoped implementation in your Superset fork: your model API, our prompts, context assembly, and UI — wired where analysts already work.

  • Scoped implementation
  • Filter-aware
  • External LLM

What we build

Three AI workstreams in Superset

Each card is a scoped deliverable in your fork — start with one or roll out the full layer over time.

How we work

Your model API, our integration

You choose the LLM provider and keep governance, keys, and policy on your side. We design prompts, pull context from chart metadata and active filters, and embed the experience in your fork’s UI.

When artifacts, search, and the analyzer ship together, the dataset → charts → dashboard description cascade enriches the index, search surfaces the right boards, and the side panel can suggest related dashboards — we scope and wire that flow in phases.

Need the system fixed fast?

Stop shipping decisions on broken numbers.

We audit what is failing, repair the foundation, and work with your team until data is reliable in day-to-day decisions.

  • Founders in the implementation
  • Clear priorities in week one
  • Fixes shipped, not just slides
  • Metric ownership made explicit
  • Pipeline failures caught early
  • BI logic aligned across teams
Priority intake

Book a focused call

Tell us where trust is breaking. We will map first fixes and ownership in one working session.

Talk to us