Reduce AI-agent token bloat by summarizing noisy tool output

Reduce AI-agent token bloat by summarizing noisy tool output targets a $2.4B = 300K engineering teams × $8K ACV total addressable market with medium saturation and a year-over-year growth rate of 18% YoY (Source: combined growth estimates for developer tools, cloud cost optimization, and AI ops adoption).

Key trends driving demand: Agent adoption — More teams are deploying autonomous agents that call tools and LLMs, creating recurring token costs and operational failures that need mitigation.; Token-awareness — Organizations are observing direct dollars tied to token consumption, which drives demand for tooling that minimizes unnecessary model input.; Edge summarization — Advances in smaller, cheaper summarization models make it feasible to compress and redact data before hitting large, expensive models.; Observability-integration — Observability and APM vendors are expanding integration points, enabling middleware to insert into existing toolchains and gain traction..