Supernova
Sync your company's tools into one encrypted data lake and query all of it in plain language through Claude or Codex, no data warehouse or data team required.
The verdict on Supernova: Giving Claude or Codex direct, natural-language access to a company's real business data Supernova's pitch works best for the team that has no data analyst and no appetite to hire one: sync the tools you already run, point Claude or Codex at one endpoint, and ask questions in plain language instead of waiting for someone to write a query. Pricing: Usage-based, no seat fees: $0.15/GB-hour compute, $0.05/GB-month storage, $0.40 per million reads, $5 per million writes.
Best For
Giving Claude or Codex direct, natural-language access to a company's real business data
Standout Feature
One MCP endpoint puts every synced tool's data in front of Claude and Codex without a separate warehouse
TL;DR
A genuinely useful shortcut for small teams who want AI-native answers from real business data without building a data stack first.
Alternatives
Fit Score: use-case reference
How this is scoredSupernova scored 1 to 5 on five dimensions for the named use cases below. Part of our catalog-wide use-case reference, not a product-quality review rating.
Giving Claude or Codex direct, natural-language access to a company's real business data
4.0/5- Capability
- 5/5
- Reliability
- 3/5
- Value
- 4/5
- Ease
- 3/5
- Compatibility
- 5/5
One MCP endpoint puts every synced tool's data in front of Claude and Codex with no separate warehouse, and the open Iceberg format with zero-copy reads avoids vendor lock-in (standout, pros). Reliability is moderate since it recently rebranded from Canvas, so the track record under the new name is still short (con).
Non-technical teams wanting a point-and-click BI dashboard with predictable costs
2.2/5- Capability
- 2/5
- Reliability
- 3/5
- Value
- 2/5
- Ease
- 2/5
- Compatibility
- 2/5
Its own cons state it's built for teams comfortable connecting data sources, not a point-and-click BI tool, and usage-based pricing needs monitoring to avoid surprise bills at scale.
Editorial judgment grounded in this tool's own published pricing, features, and our existing pros and cons, not a certification or a measured benchmark. Product quality is assessed separately under our review methodology.
Overview
Not yet reviewedProduct quality is assessed from original evidence. How reviews work.
Supernova gives Claude and Codex direct, queryable access to a company's actual data, HubSpot, Postgres, Stripe, and other connected tools, without anyone standing up a separate data warehouse first. Connected sources sync into a single encrypted Apache Iceberg data lake that Supernova's Rust-based engine serves through one MCP endpoint; point Claude or Codex at mcp.supernova.ai/mcp and every synced table becomes something you can ask a plain-language question about within roughly a minute. For teams without a dedicated data function, that means asking which customers churned last quarter and why pulls a real answer from live tables instead of waiting on a data analyst.
TypeSQL adds schema-aware SQL that autocompletes and type-checks across joins before a query runs, and every table keeps full version history so you can see what the numbers looked like before a pricing or schema change. Because the lake is stored in the open Iceberg format, any tool that already speaks Iceberg can read it directly with zero-copy connections, so adopting Supernova doesn't mean getting locked into it. Pricing is metered by actual compute, storage, and read and write volume, with no per-seat charge.
The source of the legacy catalog rating and review count has not been substantiated. Neither is presented here as a verified review rating or included in review structured data.
Workflow Fit Scores are separate, use-case-specific editorial judgments, not user-review averages. Read the Fit Score methodology.
- • No separate data warehouse or ETL pipeline needed
- • Open Iceberg format avoids vendor lock-in
- • Usage-based pricing with no per-seat cost
- • Built for teams comfortable connecting data sources, not a point-and-click BI tool
- • Usage-based pricing needs monitoring to avoid surprise bills at scale
- • Recently rebranded from Canvas, so the track record under the new name is still short
Key Features
- Encrypted Apache Iceberg data lake
- MCP endpoint for Claude and Codex
- Schema-aware TypeSQL with autocomplete
- Zero-copy reads for existing warehouses
- Full table version history (time travel)
- Single-binary CLI for sync, query, and setup
Trust & Data
Verified 2026-09
- Training on your data
- Not publishedThe privacy policy, last updated January 2026, never addresses AI model training at all despite AI agents being the core product; it only mentions de-identified analytics use. The contracting legal entity is Infinite Canvas Inc. doing business as Supernova AI, Infinite Canvas being the prior product name this catalog's own cons already note as a recent rebrand; the SOC 2 Type II claim appears only on the marketing homepage, with no audit report link, certifying body, or audit date given anywhere, notably even though the separate security page states that if a control has not been verified, it is not claimed there. Treat the SOC 2 claim as vendor-stated, not independently verified from what's published.
- Compliance
- SOC 2 Type II
- Retention
- Kept as long as necessary for the purpose or as required by law, and may extend beyond termination for fraud prevention, aggregate analysis, account recovery, or legal obligation; account content is returned within 30 days of termination on written request, though complete deletion isn't always technically or legally possible.
- Export
- Partial export
Sources: supernova.ai/privacy, supernova.ai/security, supernova.ai/terms
As published by the vendor. Verify independently before purchase decisions.
Our Take
The open Iceberg format and zero-copy reads mean you're not locked in if you outgrow it later, a fair trade for a usage-based platform this new. The tradeoff is that Supernova is infrastructure, not a finished dashboard, so a non-technical team still needs someone comfortable connecting sources and watching the pricing meter before this becomes a monthly habit.