Continuous Fine-Tuning for AI Models
AI Cost Management: Track and attribute AI spend across every provider
We build specialized LLMs for your business’s specific workflows and use cases, then continuously hone them against your success metrics, capturing your proprietary know-how in the model so it gets more valuable and harder to copy as you grow.
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 shifted from building and fine-tuning specialized LLMs for enterprise workflows (AI model development/services) to a completely different product: tracking and managing AI spend across providers (cost management/analytics SaaS). This is a full pivot to a new market, product, and problem.