Headroom Slashes AI Agent Costs by 95%—Without Losing Accuracy

AI agents are expensive not because models cost much, but because they process huge volumes of context—logs, tool outputs, code snippets. Headroom intercepts and compresses all of this before the LLM sees it, slashing token usage by 60–95% while maintaining or even improving accuracy. This removes a major economic barrier to agent adoption, making sophisticated agentic systems feasible for resource-constrained teams.