Cohesor

Cohesor

Cohesor is an enterprise control plane and gateway for AI agents that routes, compresses, governs, and observes agent requests—providing one endpoint for major model providers while enabling cost savings, per-user spend controls, and audited MCP tool access.

Cohesor is ai tools software teams evaluate for ai agents. Use this page to review pricing, integration signals, and the best alternatives before you commit.

Free API 70/100
#430 in AI Agents (430 tools)
Just launched
Data reviewed Aug 12, 2026

Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.

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Quick Overview

Best for: AI Agents

What it does

AI Tools software for decision-makers comparing workflow fit and alternatives.

Best fit

AI Agents

Pricing snapshot

Free from Gateway fee example: $10 per 100K requests gateway fee; model costs billed separately (examples shown: claude-opus-4.6 $15.00/1M, gpt-5 $12.00/1M, groq/llama-70b $0.40/1M). Cohesor shows blended example costs: Without Cohesor $8.40/1M vs Via Cohesor $3.10/1M (net of the $10/100K-requests gateway fee).

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Cohesor

Cohesor is a control plane and gateway designed for enterprise AI agents. It provides a single front door for AI model access and multi-cloud connectors, implementing a pipeline that routes, compresses, governs, and observes every agent request before it reaches a model. The platform emphasizes cost reduction (marketing claims of cutting costs and modeled savings), governance at line rate (rate limits, budget caps, and policy checks at edge), per-user attribution for spend, and privacy (prompts not retained and no training on customer data).

Cohesor targets teams and enterprises running production AI agents (support, coding, research, checkout, etc.), enabling integration with existing Anthropic/OpenAI-compatible SDKs, audited MCP tool access (GitHub, Gmail, Drive, Calendar), and dashboard observability including traces, dashboards, and audit logs.

A neutral control plane for enterprise AI agents Discussion | Link

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Key Features

Smart Routing

A lightweight classifier scores prompts and routes each request to the right-sized model based on configurable objectives (QUALITY, BALANCED, CHEAPEST, FASTEST) to balance quality, latency, and cost.

Token Compression

Lossless prompt and tool-output compression that reduces billed tokens (page examples show average reductions ~50%) while preserving semantic context.

MCP Gateway (Tool Gateway)

One audited endpoint (api.cohesor.com/mcp) for MCPs and tools; handles auth, scopes, credentials and traces every tool invocation with arguments, latency and cost.

Governance & Policy

Edge-enforced policies including gateway keys, team scopes, rate limits and budget guards that block bad requests before they reach models (policy checks in under a millisecond).

Spend Management & Attribution

Per-user and per-team spend attribution, budget caps that stop requests, weekly showback reports, and live dashboards showing spend and savings per user/API key.

Observability & Auditing

Full request traces, per-user spend, LLM routing logs, tool usage logs, exportable audit logs and dashboards for monitoring quality, routing decisions, and costs.

Unified API / One Endpoint

Supports Anthropic and OpenAI protocols natively; one URL replacement enables existing SDKs (Claude Code, Codex, opencode, LangChain) to use Cohesor with minimal changes.

Credential Vault & Tool Scopes

OAuth tokens and API keys stored in a vault so credentials are not placed in prompts or logs; enforced per-agent tool scopes for least-privilege access.

Pricing

Usage-based (gateway + model costs)

Gateway fee example: $10 per 100K requests gateway fee; model costs billed separately (examples shown: claude-opus-4.6 $15.00/1M, gpt-5 $12.00/1M, groq/llama-70b $0.40/1M). Cohesor shows blended example costs: Without Cohesor $8.40/1M vs Via Cohesor $3.10/1M (net of the $10/100K-requests gateway fee).
  • Gateway request fee (example $10 / 100K requests)
  • Pay model provider token costs (billed through Cohesor)
  • Savings from token compression and smart routing modeled per-customer

Use Cases

Support agent

Route support-bot requests through Cohesor to manage costs, enforce tool scopes (e.g., gmail:read), and audit decision traces and spend per user.

Coding agent / developer tooling

Integrate code assistants using existing Anthropic/OpenAI clients with one line of config to route, compress, and log code-generation requests while controlling spend.

Research & RAG pipelines

Compress long contexts and route expensive requests to stronger models only when needed; trace tool calls (drive.read, github.pull) and replay agent decisions.

Checkout / transactional agents

Enforce budgets, rate limits, and tool-level scopes for transactional agents and capture full traces and cost receipts for finance and audit teams.

Integrations

GitHub

MCP connector example: used for repo operations; Cohesor enforces per-agent tool scopes (e.g., repo:write) and logs each tool call.

Gmail

MCP connector example: support agents can be granted gmail:read and calls are traced and audited via the MCP gateway.

Google Drive

Drive read operations are shown in the tool call logs and are routed and traced via the MCP gateway.

Google Calendar

Calendar connector support is listed as an MCP tool example and subject to per-agent scopes and auditing.

Anthropic / OpenAI-compatible SDKs

Cohesor speaks the Anthropic and OpenAI protocols natively so existing clients (Claude Code, Codex, opencode, LangChain) can drop in with one-line config.

Model Providers (examples)

Displays routed providers and pricing examples (Anthropic, OpenAI, Google Gemini, Meta Llama, Mistral, NVIDIA, Groq, Deepseek, Qwen and others).

Benefits

Significant cost reduction through combined token compression and smart routing (platform models claim compounded savings in examples).
Governance enforced at line rate—policies and budget caps block costly requests before incurring model charges.
Single, drop-in endpoint for Anthropic/OpenAI-compatible SDKs simplifies migration with no code rewrite.
Per-user and per-team spend attribution and exportable audit logs improve financial control and compliance.
Privacy-forward design: prompts are not retained and Cohesor states it does not train on customer data.

Limitations

SOC 2: in progress (the site lists SOC 2 as 'in progress').
Adds measurable latency: architecture notes the platform path adds about 12 milliseconds at p50 (most of it the policy check).

Frequently Asked Questions

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Getting Started

  1. 1 Step 1: Sign up and create a gateway key (copy your sk-coh- key; shown once and stored as a hash).
  2. 2 Step 2: Point your agent at the Cohesor gateway by setting the Anthropic/OpenAI base URL to Cohesor (examples: export ANTHROPIC_BASE_URL="https://api.cohesor.com" or export OPENAI_BASE_URL="https://api.cohesor.com/v1").
  3. 3 Step 3: Send requests — requests are automatically compressed, routed and audited and appear in the Cohesor dashboard.

Support

docs

Documentation, quickstarts and API guides are listed under Resources / Documentation on the site.

sales / demo

Book a demo or 'Talk to us' links are presented on the site for sales and pre-sales inquiries.

dashboard / product

Product support and observability via the Cohesor dashboard (app.cohesor.com) for customers.

API

Available: Yes

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