SuperPenguin
Tracks and attributes AI spend by team, customer, and feature across every provider you bill against
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superpenguin.aiAbout SuperPenguin
SuperPenguin is AI spend intelligence: it connects to the model providers you already bill against and answers the question every team building on LLMs eventually has to face, which is where the money is actually going. Connect OpenAI, Anthropic, Gemini, Deepgram, ElevenLabs, Bedrock, Azure, Modal, LiteLLM, Together, Fireworks, OpenRouter, Vercel, or Cursor, and you get one auto-syncing dashboard with total spend, per-model breakdowns, month-over-month trends, and a projected end-of-month figure. The more interesting half is attribution. An SDK for Python and TypeScript adds two lines to your call sites and tags every request with a customer, feature, team, environment, and prompt version, so instead of a single line item for the month you can see that one customer's document-search feature accounts for a third of the Anthropic bill. That turns a cost dashboard into a product decision — which features are worth what they cost, and which customers are underwater on their plan. Reconciliation compares tracked spend against the invoice the provider actually sends and surfaces the drift, which is how untracked charges and billing errors get caught. Spend alerts fire on daily amount thresholds, day-over-day spike detection, or a monthly budget, and go to Slack, email, or Discord before the bill lands rather than after.
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Key Features
SuperPenguin Pros & Cons
✅ Pros
- +Pricing scales with managed spend, so it stays proportionate to what it saves
- +Reconciliation against real invoices catches charges a client-side tracker misses
- +Free tier is genuinely usable for a solo builder under $2K/month of spend
⚠️ Cons
- −Per-request attribution requires adding the SDK to your call sites
- −The $5K-to-$20K spend band jumps from $30 to $200/month
- −SAML SSO is still listed as coming soon
Who Is SuperPenguin Best For?
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