Think inside your AI world.

Databricks through Unl

Databricks can answer from across your lakehouse. Whether the data behind the answer meets the bar you set is your judgement — and a confident answer can rest on stale data.

Databricks through Unl reads your live lakehouse — Unity Catalog, AI Search, Genie spaces, custom functions — against the data-quality bar you have ratified, so an answer comes back trusted-or-flagged, with the quality condition it fails named.

What Databricks holds

Databricks’ managed MCP surface exposes governed data access:

  • Unity Catalog data
  • AI Search and Genie spaces
  • Custom functions and AI Gateway tools

What the naked read gives you

A naked read returns the answer Genie computes. Powerful, and it won’t tell you the source table hasn’t refreshed in a week, because “data no older than a day” is a bar you set, not a catalogue property it applies for you.

The frame judges the data it is given; it does not verify the source’s accuracy.

What changes when Databricks is read measured

Say you’ve ratified a data-quality bar: any answer used for a decision must rest on tables refreshed within 24 hours and with no failed quality checks.

“Can I rely on this figure?” returns, measured: flag — the figure is computed correctly, but its source table last refreshed 40 hours ago, past the freshness bar you set so decisions aren’t made on stale data. Databricks supplied the answer; your ratified bar supplied the quality check and the reason.

And back again

When you accept a weekly-refresh table as fit for a particular report and record it, the next read holds that report to the exception you settled.

The answer comes back measured against what you already decided, and why.

The lane is live and open to this tool today: one box, paste anything. If it speaks MCP, Unl can reach it. Readings arrive unprompted, the data beside the criterion; Unl is a courier, not a warehouse, and keeps only your keys and the frame.

Questions people ask

Can AI check Databricks answers against a data-quality bar?

Yes, through Unl. You ratify the bar (freshness, passed quality checks, with reasons), and a Databricks read is measured against it — the answer returns trusted or flagged, with the condition it fails named.

How do I connect Databricks to Claude?

Databricks offers a managed MCP server over Unity Catalog, AI Search and Genie. Through Unl the same reads arrive measured against your ratified quality bar, so an answer reads as reliable-or-flagged.

Does Unl modify my lakehouse?

Unl reads through Databricks, and can write back on your explicit gesture — it never acts as a side effect of a read.

What this is

Think inside your AI world — you stay in command

Unlimitless (Unl to friends) holds what you've settled, reads what your tools are showing, and catches what's changed out in the world — and hands your AI whatever bears on the work, the moment it's needed, without you asking. The right thing, in front of the model, unprompted, with you in command of the call. So you keep moving toward what you set out to build, on top of everything you've already decided.

It plugs into Claude, Claude Code, ChatGPT and Cursor as an MCP connector. Quick to connect, in a couple of steps.

Unlimitless is open now to invited Alpha. Apply for the Beta waitlist to come in ahead of the full launch:

Alpha is invite-only · free at launch.