Caveman

Caveman is an AI efficiency operating stack built to cut the cost and context size of agent-native development. If your agents burn through tokens on verbose logs, bulky JSON, and oversized tool outputs, Caveman compresses all of it before calls ever reach your provider.

The stack includes an MIT-licensed skill, a free local proxy, and an Agent SDK, with cloud and enterprise services planned for the future. Whether you are running local experiments or scaling production workflows, there is a layer that fits how you work.

Compression covers logs, JSON, code, diffs, tables, tool outputs, and files, and every original byte stays fully recoverable, so nothing is lost in the process. You get the savings without giving up fidelity.

Beyond compression, Caveman supports caching, eval-gated model routing, clear token usage visibility, savings estimates, and verification workflows, giving you the tools to understand and control exactly where your tokens and budget go.

The local wrap works with your own provider keys and requires no Caveman account, so you can start reducing costs right away while keeping full control of your setup.