What Portals AI does

Connect the data you already have, agree on what it means, ask it questions in plain language, and extend how far the agent can go.

Connect anything you already have

CSV and Excel files, Google Sheets, Excel on OneDrive, and REST APIs — bring in the data you already work with. Re-sync a connection whenever its source changes.

Agree on what the fields mean

Map every source onto a shared vocabulary — types, validation, and canonical formats — so three systems spelling a date three ways stop being three problems.

Ask, don't query

Open a portal and ask in plain language. It answers with tables, charts, maps, and prose built from your live data — and you pin the results worth keeping.

Share it with the right people

Every station, view, and pinned result has an owner, and you decide who else can see or change it. Permissions are checked on the server for every request, so what the app hides it also refuses.

Run it in your own cloud

Enterprise teams can run Portals AI on their own Kubernetes cluster, so the data, the database and the people who can reach them all stay inside their own environment.

Extend what the agent can do

Start with a portal's built-in reasoning, then add more. Toolpacks give the agent new capabilities — turn them on per station and it uses whatever's available.