For finance and operations teams
Your team already builds dashboards with AI. Now share them safely.
Dash On turns them into one hosted link: connect your database and each person sees only their slice, with every open on the record.
How it works
From your assistant to your co-workers
- Bring your own dashboard: the HTML file you built with AI, with Claude or ChatGPT, say, exactly as it is - nothing to rebuild, no code.
- Connect it to your live data: point it at your database, so the numbers stay current without re-exporting the file.
- Control who sees what with row-level security: each person sees only the rows their own rules allow - Ana sees East, Lee sees West - built into the query on the server.
- Publish it for your team: previewed as two different people before it goes out, then shared as one link, with every open, every refusal and every access change recorded.
What you get
Shipped, not just shared
What comes out is scoped, reviewed, audited and answerable.
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Scoped by construction
A viewer's rows are built into the database query, on the server, from their rules - never trimmed out of a bigger result afterwards. Empty rules return zero rows, never all rows.
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Preview as two people before anything ships
Before a live dashboard can be published, you open it as at least two different viewers, through the real query path - not a simulation - and see exactly the numbers each will see.
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An audit trail you can read
Every open, every refusal, every access change is on the record and answerable on a screen in under a minute - who saw what, when, and what changed.
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Kept apart from everything else
An uploaded dashboard is treated as untrusted code. Each one runs on its own separate web address, walled off from the platform and from every other dashboard.
Ready to share your first dashboard?
Access is by invitation: a builder invites the people who may open a dashboard, and signing in is how an invitation is completed.
The names and numbers in the illustration are made up, and the full demo - two people getting different rows from one link - runs against a fully synthetic dataset. Nothing shown is ever a real company's data.