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AI Cost Management: Track and attribute AI spend across every provider
The problem: AI spend is scattered across multiple provider billing consoles that don't talk to each other. Teams can't answer simple questions like "which customer is driving our Anthropic bill?" or "is this feature profitable after AI costs?" without manually pulling data from each provider and stitching it together in a spreadsheet. What SuperPenguin does: SuperPenguin tracks AI spend across 14 providers (OpenAI, Anthropic, Deepgram, ElevenLabs, Modal, Cursor and more). Zero-code setup: connect an API key and costs sync automatically with model-level breakdowns, trends, and forecasts. Per-request attribution: add two lines of Python SDK to tag every AI call by customer, feature, or team. Slack alerts on budget thresholds and spend anomalies. Most teams are set up in under five minutes. We help companies see where their AI money goes and whether it's worth it.
Carrot Labs positions itself as an AI cost management platform that tracks and attributes AI spend across multiple providers, with per-request granularity, forecasting, and reconciliation. It emphasizes visibility into spend by customer, feature, team, and prompt version, with alerts and dashboards.
Connects to multiple AI providers (OpenAI, Anthropic, Google Gemini, AWS Bedrock, Deepgram, ElevenLabs, Vercel AI Gateway, LiteLLM, and more) to aggregate total AI spend in a single dashboard. Provides per-provider and per-model spend breakdowns, invoice reconciliation, Slack alerts, and live dashboards. Offers per-request attribution via a lightweight SDK (Python/TypeScript) to tag and track cost by customer, feature, team, and environment, with on-demand forecasting and spend analytics. Also supports integration with Cursor for PR cost attribution and ROI insights, and includes onboarding with a five-minute setup.
Who it’s for: Companies and teams that build or operate AI-powered products and services and need visibility into AI spend across multiple providers (engineering, finance, and product leaders).
Product features and pricing are clearly defined; multiple provider integrations and an SDK indicate product-market fit and active development; pricing tiers and mentions of onboarding suggest growth traction and scalable adoption.
Carrot Labs Founder. Building the continuous learning platform for AI Agents https://carrotlabs.cal.com/chris/20-min-meeting
Co-Founder of Carrot Labs. Previously Senior Data Scientist at Snowflake, where I was in charge of ML account-based bookings forecasts that shaped financial planning as the company scaled from $250M pre-IPO to $3.6B in revenue.
Your model is your moat. Stop renting your intelligence and start growing it.
Carrot Labs provides a platform to build proprietary, task-tuned base models from open-source foundations, continuously retraining as data flows in to outperform frontier models for individual agents. It targets startups building AI agents seeking faster, more accurate performance and a distinct competitive advantage through customized models.
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