AI business intelligence
An AI business intelligence platform
The reporting layer stays. What changes is who has to build something before a question gets answered.
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AI Business Intelligence Platform
Supaboard is an AI business intelligence platform: an agent reads your schemas, writes the query when the question is asked, and returns the answer with its derivation attached, instead of an analyst modelling data and publishing a dashboard that anticipates the question. 700+ sources, 123 connectable unaided, $83 per user per month billed annually.
The honest version of the category claim is narrower than the marketing version, and it is worth stating before the feature list. AI has not made data modelling, governance or data quality go away, and any vendor implying otherwise is selling you a future incident. What it changes is the cost of the long tail — the thousands of questions a year that were never worth a ticket and so got answered by guesswork or not at all.
Looking for how this works in general rather than what we built? What Is Business Intelligence? Complete Guide for Businesses covers it.
What actually changes
Three things worth separating from the noise, because they are the ones that survive contact with a procurement process.
- Questions no longer need to be anticipated. The unit of work stops being the dashboard and becomes the question, which means the backlog stops being a queue of build requests.
- The derivation travels with the answer. This is the part that makes the rest usable in a company where numbers have consequences — a chart you cannot trace is a chart nobody will defend in a meeting.
- Context is a configurable artefact. Business rules, glossary terms and past corrections live somewhere and get applied automatically, rather than living in one analyst's head.
What has not changed
Garbage in still produces garbage out, faster and with more confidence than before, which is worse. If two systems disagree about what a customer is, an agent will pick one and sound certain about it.
Governance still matters, and arguably more: a tool that lets four hundred people query production needs read-only enforcement, row-level access and an audit trail, or it is a data-loss incident waiting for a slow afternoon. And someone still has to own the semantics. The difference is that they encode them once as rules an agent applies, rather than re-encoding them in every report.
What an AI BI platform has to have
A checklist that survives a security review, rather than a feature list.
- Read-only by construction. Supaboard's query layer rejects DDL and DML before the statement reaches your database, and we ship the SQL to create a read-only user per source.
- Breadth of connection. 700+ sources in the catalogue and 123 connectable unaided, because the questions that matter rarely respect the boundary of the warehouse.
- Visible queries and correctable answers, so a wrong number becomes a fixed rule instead of a lost argument.
- A deployment story your security team can accept. SOC 2 Type II on Business and Enterprise, HIPAA BAA Enterprise, add-on on Business, and a single-tenant on-premise option with no data egress and your own model provider keys.
- Somewhere for the answer to go. 20+ chart types, dashboards, 3 export formats and scheduled delivery — an insight that stops at the screen it was found on has not finished.
Where conventional BI is still the better buy
If your reporting is stable, your data is modelled and your questions are known, a conventional BI tool does that job for less money — Power BI seats start at a fraction of any AI-native platform, ours included, and Metabase's open-source edition is free.
The case for AI BI is not that it is better at building dashboards. It is that most companies have a backlog of questions that never became dashboards, and that backlog is where the cost actually sits.
Teams who did this
Frequently asked questions
What should we require from an AI BI platform?
Read-only enforcement at the query layer, enough connection breadth to reach the systems the questions actually live in, a visible query on every answer, a deployment model your security team will approve, and pricing that does not punish adoption. Anything that fails one of those five will fail the rollout rather than the demo.
Does AI BI replace dashboards?
No. Recurring, governed reporting is still best served by a dashboard, and Supaboard builds those too. What changes is that a question does not need a dashboard built before it can be answered.
Is it safe to let non-technical staff query production data?
Only with read-only enforcement and access controls. Supaboard rejects every write statement at the query layer before it reaches your database, connections are encrypted per workspace and never returned to a client, and Enterprise adds role-based access and audit logs.
How is this different from asking ChatGPT about a spreadsheet?
A general model reasons over whatever you paste. An AI BI platform connects to the live system of record, applies your business rules, runs a real query and shows it. You can also reach Supaboard from Claude or ChatGPT over MCP, read-only, if that is where your team already works.
What does AI business intelligence cost?
Supaboard is $83 per user per month billed annually on Individual and $208 on Business, with a 14-day free trial. Usage credits are included in the seat rather than metered per query.