AI answers what. You still answer why.

DBx Studio collapses the hours between a question and a number — and keeps the reasoning visible, so the part that needs judgement still gets it.

Every organisation has more data than it uses. The constraint was never storage or compute — it's the human effort between a question and an answer someone will act on. Finding the right tables. Writing the query. Checking it. Charting it. Sharing it. Waiting.

The bottleneck is rarely the database. It's the workflow around it.

What changes

Ask, don't translate

Questions go in as plain English. The schema reading, SQL writing and execution happen underneath, and the query stays visible beside the answer.

Follow the thread

Analysis is iterative — one question becomes five. Follow-ups continue the same session instead of restarting it, so filters and definitions carry across turns.

Experts go faster too

Complex joins drafted, unfamiliar queries explained, errors caught before execution. Less troubleshooting, more analysis.

The queue shrinks

Routine questions move to the people who have them. Analysts get their week back for the work that actually needs an analyst.

The division of labour

AI answers

• What happened?
• When did it happen?
• Which metrics changed?

Fast, repeatable, checkable — and only as good as the context it's given.

You answer

• Why does it matter?
• What should we do next?
• What is it worth to us?

Judgement, context and consequence. This half was never the bottleneck, and it isn't going anywhere.

How it works

01

Connect

Point DBx at the database or warehouse you already have. No migration, no new warehouse, no pipeline to build.

02

Curate

Publish the views and metric definitions people should query. This is the step that decides accuracy, and it's usually a day's work for the metrics that matter.

03

Ask

Your team asks in plain English and gets a table or chart back, with the SQL beside it and good queries saved by name for reuse.

Speed is worth nothing if the number is wrong

A generated query runs identically whether or not it means what you meant — there's no error for joining at the wrong grain or filtering on the wrong date column. Which is why most of DBx is the part that isn't the model:

Context, not guesswork

Business terms resolve through a semantic layer to definitions your team agreed on, rather than to whichever column name looked closest.

Validated before it runs

Queries are checked against what they're permitted to touch and what they'll cost before execution — not after.

Read-only by privilege

Enforced by the database role and row-level policies, so access holds regardless of what any query asks for.

SQL always visible

Every answer shows the query that produced it. Anyone who can read SQL can check it, and good ones get saved and reused by name.

The goal was never a faster query. It was shrinking the distance between a question and an answer you can trust.

What people ask first

Is it safe to point this at production?

The controls sit in the database, not the AI: a read-only role, access granted only to curated views, row-level security carrying each user's identity, statement timeouts and cost limits. A prompt instructing a model to behave is not an access control.

Do we still need analysts?

Yes — for different work. Routine, repeatable questions move to the people who have them. Defining metrics, curating what's query able, and reviewing the queries behind consequential decisions stay where they are.

How long until it's useful?

Connecting takes minutes. Getting accurate answers depends on curating views and agreeing metric definitions — start with the five metrics your teams argue about and the rest follows.

See it on your own schema

Bring ten questions your team asks every week and already knows the answers to. Run them against your own schema and count how many come back right — a more useful evaluation than any demo, including ours.

If we score badly on the ones that matter to you, better you find out in an afternoon than after a rollout.

Query it. Analyze it. Visualize it. — all with DBx.