Ask your warehouse in plain English.
A defensible Databricks Genie deployment — every answer comes from a certified gold layer, ships with the SQL it ran, respects Unity Catalog row + column masks, and is gated by an eval suite before any change reaches users.
Most NL-to-SQL tools are demo-good, not deploy-good.
Generic NL-to-SQL chatbots are easy to demo and hard to defend. They guess schemas, ignore business definitions, hide the SQL they ran, and answer the same question two different ways on consecutive Mondays.
The defensible version is Genie pointed at a certified gold layer, with a metrics + glossary semantic surface, full SQL transparency, per-user identity, and an eval suite that gates every change. The work isn’t in the chatbot — it’s in the data layer underneath. That’s what we build.
The shape of a trustworthy Genie.
Questions come in from web, Slack, Teams, or API. Genie plans against the certified gold layer + glossary, generates editable SQL, runs it on serverless DBSQL, and returns a cited answer. Unity Catalog governs the lot — identity, masks, lineage, audit, and per-query cost.
Six capabilities that make it defensible.
Certified gold tables
Genie answers only from the data you’ve certified. We build the gold layer first so analysts and business users get answers from one canonical source — not whichever table is closest.
Metrics + glossary
A semantic layer with canonical metric definitions, synonyms, and business glossary prompts. "Active claim", "FY", "open period" mean the same thing every time.
NL → SQL with citations
Every answer shows the SQL behind it, the tables it touched, and the rows it returned. Editable, copyable, defensible — never a black box.
Multi-surface delivery
Native Databricks Genie space, Slack and Teams integration, embeddable web widget, and a server-to-server REST API for tooling.
Unity Catalog governance
Per-user identity via Entra ID. Row and column masks apply. Every question and answer is audited. Cost attribution per query.
Eval suite
A pinned set of questions with known-good answers, run on every change. Accuracy gates before promoting any model or schema change to production.
Built for you if…
- 01
You have a governed lakehouse already (Databricks, Fabric, Snowflake) and want the answers in plain English without the gold layer turning into spreadsheet exports.
- 02
Your analysts spend more time answering 'can you pull X for me?' questions than building real models — and you'd like to give that work back.
- 03
You need every answer to be defensible: who asked, what SQL ran, which rows, when. Not a black-box chat with the warehouse.
- 04
You're cautious about NL-to-SQL accuracy and want a real eval framework that gates changes, not vibes.
- 05
Australian-hosted, identity-aware, with usage and cost visible per user and per query.
Data first, chatbot second.
We do the unglamorous work first — certify the gold layer, define the metrics, write the glossary — then stand up Genie on top.
- — 01
Certify the gold layer
We start with the data, not the interface. The first 2–3 cycles harden a small certified gold layer with metrics + glossary so Genie has somewhere honest to plan against.
- — 02
Stand up the Genie space
Genie space scoped to those certified tables, glossary loaded, eval suite seeded with the questions that actually matter to your business.
- — 03
Roll out + tune
Beta inside a small team, tune prompts and synonyms with real questions, then expand to Slack / Teams / embedded surfaces. Eval suite gates every change after launch.
Common questions.
Conversational data, done defensibly.
Send a brief and we’ll reply within one business day with a scoped response — and only take it on if we can ship something you’ll trust.