Supaboard is an AI data analysis tool positioned as an AI data analyst that connects business data, letting users understand data changes and their causes through natural language questions, rather than stopping at static dashboards. Its official website states that it once ranked first in the Product Hunt weekly list in February 2026, with a G2 rating of 4.8 (based on 3 reviews).
I. Purpose Supaboard is used to answer questions like "what happened and why it happened," turning a single exploration into reusable reports, dashboards, and automated monitoring. The official website emphasizes that traditional dashboards only track the questions you have already decided to ask, whereas Supaboard helps explore the questions that emerge later. Example flow: a user asks "Why did the West decline last month?", and the system answers that overall revenue grew 7%, but the West declined 20% (from $70,000 to $56,000); on follow-up, the breakdown shows gross sales stayed flat at $75,000, while refunds rose from $5,000 to $19,000; further drill-down locates delayed-order refunds rising from $2,000 to $16,000; finally, an alert is set to email the team when delayed-order refunds rise again. The official website notes that this example is based on sample data, and actual answers start from the data the user connects.
II. Main Capabilities
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Natural language Q&A: Ask questions in the app, in Slack, or in Claude, with answers accompanied by the query behind every number, checkable in one click.
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Business definitions and memory: The Agent can load rules, definitions, and caveats by table, understanding what the team means by terms such as "active customer"; telling the Agent a rule once in chat (such as excluding suppliers that failed compliance) saves it to memory and applies it automatically; evals can also be used to assess the Agent's performance with questions that have known answers.
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Real-time dashboards and Live Datasites: After describing what you want to monitor, the system automatically selects charts, connects real-time data, and lays it out as a board, or generates a complete data site with a shareable link.
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Embedding: Embed into your own product via a single iframe, and you can decide which filters viewers control and whether the page requires a signed token before loading.
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Chart insights: Next to each chart, the changes are automatically described, including which segment moved, by how much, and what it means if the trend continues.
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Scheduled reports: Describe a report once, and it runs on a schedule and directly generates a written report.
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Run history: Every run has a log where you can see when it was triggered, what each step returned, and why.
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AI Analyst Steps: Add an Ask Analysts step to the workflow so that on every trigger the AI analysts automatically answer again from live data.
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Alerts: The example mentions being able to set up an alert that checks for delayed order refunds and emails the team when they rise again.
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Connectivity: The official website states that it supports 12 databases and data warehouses, querying at question time; reads 22 applications via MCP; and does not pre-sync or copy. Questions can be asked from Slack and MCP clients.
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How to use The official website offers a free plan, no credit card required, and a 30-minute demo can be booked. After users connect a database, application, or tool, they start by asking questions in natural language. Specific installation and integration configuration steps are not provided in the existing materials.
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Security and compliance The official website states that the query layer is read-only by design, credentials do not leave the workspace, and every query is logged; connection credentials are encrypted at rest, scoped by workspace, and are not recorded or returned to the browser. The query layer rejects DROP, INSERT, UPDATE, and other write operations before they reach the database. It complies with GDPR, SOC 2 Type II (report available under NDA), and HIPAA (BAA available). Secure Integrations uses verified variables to scope each query to the signed-in user's own data.
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Use cases and results The official website lists: Jindal Healthcare handed exploratory analysis to the Agent, reducing total analysis cost by 90%; Objection AI shortened exploratory analysis from 2 days to 4 minutes; and on BI Bench the correct answer rate is 97.8%. Customer reviews come from people at companies such as Netlify, JindalX, and The Primary.
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Limitations The existing materials do not provide specific pricing, the feature limits of the free plan, the complete list of supported databases and applications, deployment methods, language support, and other details; this information is not currently available.