Intellrise

Intellrise is an AI data analyst aimed at small data teams. Users connect a database or spreadsheet, ask questions in plain language, and get back the generated SQL, a chart and the underlying table. Answers can be refined through follow-up chat, for example by adding a profit-margin column or grouping by month, and any result can be pinned to a dashboard or folded into a report.

For more involved questions, Intellrise shows a readable query plan covering sources, joins, filters and aggregation, which can be approved before anything runs. A single question can join across connected sources. A semantic layer annotates tables and columns automatically and keeps meanings that users clarify in chat, so field definitions persist between sessions and stay with the team when people leave. Teams using dbt can point it at their mart schemas.

Supported data sources are PostgreSQL, MySQL, Redshift and Google Sheets, plus CSV and Excel uploads on paid plans. Reports export to CSV, Excel, PDF, Word and PowerPoint, and Pro adds scheduled email delivery and read-only share links that viewers can open without an account. Model access is bring-your-own-key: Google Gemini, OpenAI, Anthropic or any OpenAI-compatible endpoint, with no credit system or question cap from Intellrise itself.

Pricing starts with a Free plan (one user, one data source plus Google Sheets, three dashboards). Pro is $29 per month or $290 per year and unlocks unlimited sources, dashboard customization, schema learning and email delivery. Team is $100 per month for five seats with extra seats at $20 each, and adds shared sources and an organization-wide AI key. A Managed plan at $490 per month has the vendor connect and sync data, run the analyst and include AI usage, with the first two weeks free. Enterprise terms are custom.

Intellrise sits between notebook-style analytics tools such as Hex and spreadsheet-centric AI helpers such as Formula Bot or Coefficient. Its narrower connector list makes it a better fit for teams already on a common SQL database than for organizations with many SaaS data sources.