AI Agent Cost Optimizer
An analytics platform that tracks AI agent spending across LLM providers (OpenAI, Anthropic, Google, open-source) and automatically recommends cheaper model routing, prompt compression, and caching strategies to reduce costs.
🎯The Problem
Companies running AI agents at scale are shocked by their LLM bills. A single agent workflow might cost $0.50 per run, and at 10,000 runs/day that's $5,000/day. Teams have no visibility into which steps are expensive or which could use cheaper models.
💡The Solution
A proxy layer that sits between agents and LLM providers, tracking cost per step. ML-powered recommendations suggest which steps can use cheaper models (GPT-4o-mini instead of Claude Opus), where prompt caching helps, and where responses can be cached entirely.
👥Target Users
Engineering managers, AI platform teams, startups scaling agent-based products, finance teams approving AI budgets
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