Supernova

About Supernova

Supernova connects a startup's live data to Claude and Codex, letting users ask questions, investigate performance, and run analysis inside those AI tools. It syncs data from Stripe, HubSpot, PostgreSQL, and 30+ other apps into a data lake, so queries run on current data without moving everything into a traditional BI stack. The tool is open source and includes a CLI.

Review

Supernova sits between your operational apps and the AI assistants you already use. Instead of exporting CSVs or building ETL pipelines, you connect your sources once and then query them through Claude or Codex. The makers launched the product on Product Hunt with a 20% discount for the first six months, and they report cutting data costs by 80-90% for customers who switch from other platforms.

Key Features

• Direct connections to Claude and Codex via MCP, so the models can query your live data natively.
• 30+ app integrations including Stripe, HubSpot, and PostgreSQL, with full dataset syncs from each source.
• Table-level permissions that let you control which data each person or MCP can see, such as "Allow only salesforce.opportunities" or "Allow all tables except postgres.users".
• Built-in git version history for dashboards and durable models, enabling多人 collaboration on data projects.
• Iceberg exports and a CLI for working with the data outside the main interface.

Pricing and Value

Pricing details are not fully published in the reference material, but the makers state the tool is "crazy affordable compared to alternatives" and cite 80-90% cost reductions for customers migrating from other data platforms. A launch promotion gives 20% off for six months. If you connect directly through the MCP, you can use your existing Claude subscription rather than paying Supernova for token usage. The tool requires payment to use after the initial setup.

Pros

• Queries run on a synced data lake, so even million-row datasets return results in about a second rather than syncing on demand.
• Data from different sources can be joined in one query, such as combining Stripe invoices with Salesforce customer records.
• Permission controls let you restrict table access per user, which addresses governance concerns for sensitive data.
• No separate data warehouse or ETL tooling is required; the data lake and sync machinery are included.
• The open-source nature and CLI give technical teams flexibility to script and automate workflows.

Cons

• AI models can misread data even when it's in context; the makers recommend an adversarial review workflow for important numbers, and they acknowledge manual review is still needed for board-level reporting.
• Rate limits vary by data source, so sync machinery has to adapt to each platform's constraints, which can introduce delays for some integrations.
• The tool is not well suited for teams that need a traditional BI dashboard with a fixed, governed interface, since it's built around AI chat interactions and requires trust in model outputs.

Supernova fits startups that already use Claude or Codex heavily and want those tools to answer data questions directly. It works best for teams with technical resources who can set up integrations and review AI-generated analysis. Companies with strict data governance requirements beyond table-level permissions, or those needing a self-contained BI front-end, should evaluate whether the AI-centric workflow matches their needs.

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