Cohesor

A neutral control plane for enterprise AI agents

SaaSDeveloper ToolsArtificial Intelligence

▲ 81 votes3 commentsLaunched Aug 12, 2026

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Cohesor is the neutral control plane for AI agents. It sits between your agents - Claude Code, Codex, Cursor, agentic workflow and every LLM model: compressing ~50% of tokens, routing each request to the right-sized model, and governing spend per user for your team. One endpoint, zero code changes, 60–90% lower agent bills. Agent spend is exploding with almost no tooling to understand or control it. The neutral, cost-first control layer is the empty quadrant. Cohesor is built for exactly that.

AI Analysis

📝 Summary

Cohesor is a neutral control plane for enterprise AI agents, positioned between agents like Claude Code, Codex, Cursor and various LLM models. Core features include ~50% token compression, intelligent routing to right-sized models, per-user spend governance, and a single endpoint with zero code changes. It solves the critical pain point of exploding agent costs lacking monitoring or control tools. The USP is its cost-first, neutral approach delivering 60-90% lower bills. Overall value proposition: efficient governance and significant cost savings for teams scaling AI agents without infrastructure overhaul.

📈 Market Timing

In 2025-2026, AI agents and agentic workflows are rapidly scaling in enterprises, with LLM usage exploding and costs becoming a major concern. Technology for routing, compression, and observability is maturing while economic pressures demand optimization. User demand for cost control tools is surging amid AI adoption boom. This is a highly favorable time as the market needs exactly this type of governance layer before spend gets out of control. Excellent Timing.

✅ Feasibility

Technically feasible leveraging existing LLM proxy, routing, and prompt compression technologies. Moderate development and operation costs for a cloud SaaS. Compliance risks around data privacy for enterprise AI traffic; scalability is high via cloud infrastructure. Requires AI expertise but aligns well with current dev tools ecosystem. Overall rating: High, with strong potential once core routing and compression are proven.

🎯 Target Market

Main target: Enterprise engineering and AI teams using multiple agents and LLMs (developers, product teams). Industries: Tech/software companies, finance, healthcare adopting AI. Geographic: Primarily US and Europe-based enterprises. Estimated TAM: Part of $10B+ AI infrastructure/DevTools market; SAM for LLM cost optimization ~$500M+, SOM growing with agent adoption. Core pains: uncontrolled spend and inefficiency. High willingness to pay due to direct 60-90% cost savings.

⚔️ Competition

Medium. Direct competitors: 1. LiteLLM (litellm.ai) - LLM proxy/routing. 2. Helicone (helicone.ai) - LLM observability and cost tracking. 3. Portkey (portkey.ai) - AI gateway with guardrails. 4. LangSmith (smith.langchain.com) - debugging and monitoring for agents. Advantages: Agent-specific focus, token compression for 50% savings, per-user governance, zero code change emphasis. Disadvantages: Newer player with potentially narrower feature set vs. broader observability platforms; needs to prove enterprise reliability.

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