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SuperPenguin

Tracks and attributes AI spend by team, customer, and feature across every provider you bill against

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freemiumDR 21Priced on the AI spend you manage through it, not seats. Free $0/mo covers up to $2K managed spend with all dashboard features, SDK attribution, and reconciliation. Growth $30/mo up to $5K managed spend adds 3 team members and cost alerts. Pro $200/mo up to $20K managed spend adds 10 members, spend forecasting, and Cursor PR cost attribution. Enterprise is custom above $20K with unlimited members. No card required to start.View full pricing →

Visit SuperPenguin

https://superpenguin.ai/

About 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

Auto-syncing dashboard across 15+ model and infrastructure providers
Per-request attribution by customer, feature, team, environment, and prompt version
Invoice reconciliation that flags drift between tracked and billed spend
Spend alerts on thresholds, spikes, and monthly budgets to Slack, email, or Discord
Two-line Python and TypeScript SDK
Month-over-month trends and end-of-month spend forecasting on Pro

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?

👤Teams whose model bill grew faster than their understanding of it
👤Usage-based SaaS that needs per-customer AI cost to price correctly
👤Finance and engineering leads reconciling provider invoices

Tags

ai cost managementllm observabilityfinopsspend trackingattribution
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