Shadowfax
AI-native analytics with repeatable analyses and an audit trail that survives exec review — no Python required
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shadowfax.aiAbout Shadowfax
Shadowfax is an AI-native analytics platform built around a specific objection: spreadsheet copilots and vibe-coded notebooks produce answers that cannot survive a CFO review, because AI said so is not a defence when someone asks how a number was derived. Shadowfax turns messy data into repeatable, interactive analyses with an audit trail you can explain in an executive meeting, and it does it without requiring Python — which is the constraint that keeps most analyst backlogs from clearing. The framing throughout is the daily analyst's problem: another complex request lands, the backlog grows, the spreadsheet copilot fails again, and manual work wins by default. Repeatability is the operative word: an analysis you can re-run when the data updates is an asset, while a one-off chat that produced a chart is not. It is in public beta, with a free tier that includes all core features, standard usage limits, basic data sources and standard rate limits at no cost — which is an unusually complete free offer and reflects the beta stage more than a permanent commitment. Pro is announced at $20/month for more usage, advanced data sources, priority email support and higher rate limits, but is listed as coming soon rather than purchasable today, and Enterprise adds custom limits, SSO/SAML, advanced security and compliance, data residency and regional deployment. Being in beta with an unlaunched paid tier is the main risk to weigh.
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Key Features
Shadowfax Pros & Cons
✅ Pros
- +The defensibility angle is the real blocker for AI analytics in finance teams
- +Free tier includes all core features rather than a crippled subset
- +Repeatability makes an analysis an asset instead of a screenshot
⚠️ Cons
- −Public beta — not proven on production reporting
- −The $20 Pro tier is announced but not yet purchasable
- −Free-tier generosity is a beta artefact and likely to tighten
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