Supernova

The short version: if your team already lives in Claude or Codex and wants to ask real business questions without waiting for a data team, Supernova is a clever, low-friction way to get there — the usage-based pricing keeps it cheap at small scale but requires some care once volume grows.

Compared to building a traditional BI stack with a warehouse like Snowflake or BigQuery plus a visualization layer like Looker or Metabase, Supernova's advantage is skipping most of that setup — you connect sources and query in natural language through an AI assistant you already use, rather than learning a new dashboarding tool. The tradeoff is usage-based pricing with no flat cap: predictable for light usage, but worth watching closely as data volume and query frequency scale, since costs compound across compute, storage, operations, and AI token pass-through simultaneously. For an early-stage company without a dedicated data team, that's still likely far cheaper and faster than hiring for or building a warehouse from scratch; for a company already running a mature BI stack, switching costs may not be worth it unless the Claude/Codex-native querying is specifically what you're missing.