Caveman

Caveman provides the tools and infrastructure to run AI agents with fewer tokens, less compute, and lower cost. It offers a cloud and local runtime where developers can observe traffic, measure costs, and apply improvements to their agent runs. The platform supports a range of coding agents and lets teams control how requests are routed and processed while watching the impact on bills.

Caveman reads less, says less, and picks the model. It compresses eligible context, reduces input and output tokens, and adaptively selects the cheapest model that still solves the task. The system keeps the original data available for recovery when needed.

Caveman offers different plans and deployment options including cloud hosted, VPC, on-prem, or local tooling. It describes platform integrations and limits such as supported agents, logging, and governance controls, as stated across the pricing, platform, and docs pages.

Use cases

• Measure cost per task and reduce waste