Observe
Accept compatible agent and application traffic, then understand the context entering the workflow.
Context efficiency for serious AI work
Send models less context. Keep what matters within reach.
CutCtx is a local-first control layer for AI agents and LLM applications. Reduce context overhead, retain access to useful information, and measure the result on your own traffic.
Local-first · Provider-flexible · Measured on your workload
Illustrative workflowEvaluation active
Incoming contextAgent history + tools
CutCtxCompress + retrieve
Selected modelFocused payload
Useful context retained
Provider route preserved
Report available
Fits the providers and agent workflows your engineers already use
OpenAI
Anthropic
Gemini / Vertex
Amazon Bedrock
Chosen endpoint
Claude Code
Codex
Cursor
Cline
Aider
One control loop
Context efficiency you can inspect, not merely assume.
CutCtx works around the workflow you already have, preserving your provider choice and making the result observable.
Compress
Reduce unnecessary context overhead with protocol-aware controls before the request reaches the model.
Retrieve
Keep useful information accessible through retrieval, memory, and cache-aware context controls.
Prove
Use telemetry and savings reports to evaluate the operational result on your own traffic.
Built for the real workflow
A context layer that stays out of your way.
Start with the part you need today. Keep provider routing, deployment, and evidence under your control as the rollout grows.
Context control
Reduce overhead without losing the thread.
Protocol-aware compression works with retrieval, memory, and cache-aware controls so useful information remains available when the workflow needs it.
context → classify → compress → retrieve → model
Fits your stack
Keep the agents and providers you already use.
Wrap supported coding agents and route compatible OpenAI, Anthropic, Gemini/Vertex, Bedrock, and chosen-endpoint traffic through one control layer.
Operational evidence
Inspect the result on your traffic.
Use the local dashboard, telemetry, and savings reports to understand the result before selecting a commercial path.
Deployment control
Start locally. Deploy where your environment requires.
Use the CLI and local proxy, Docker or Docker Compose, Kubernetes, or an air-gapped deployment path.
Local CLIDockerKubernetesAir-gapped
Evaluation to evidence
Make the next decision with your own report.
CutCtx is designed for a low-friction technical evaluation. Use a workflow you already trust, then inspect what changed.
Install
Add CutCtx locally without replacing your agent or provider.
Wrap
Route a supported coding agent or compatible application through the proxy.
Run
Use the workflow normally so the evaluation reflects real traffic.
Inspect
Review telemetry and the savings report before you decide how to scale.
Control stays close
Local-first by default. Flexible when the deployment grows.
Processing stays in your environment by default, requests go to the model provider you configure, and commercial controls can support broader organizational needs.
Customer environment
Run locally or in customer-managed infrastructure rather than depending on hosted prompt analytics.
Chosen provider
Keep OpenAI, Anthropic, Gemini/Vertex, Bedrock, or the compatible endpoint selected by your team.
Governed scale
Add shared reporting, policy, identity, audit, retention, and deployment support when the organization needs them.
A path for each stage
Evaluate freely. Add coordination and governance deliberately.
Builder
Prove the workflow locally.
Core compression, proxy, CLI wrapping, SDKs, MCP, local dashboard, and Docker.
Team
Share evidence and policy.
Shared analytics, savings reports, policy presets, budget controls, and support.
Enterprise
Operate with governance.
Identity-aware administration, RBAC, audit export, retention controls, fleet APIs, and deployment support.
Start with evidence
Run CutCtx on the workflow you already have.
Install locally, wrap an agent, and inspect the result on your own traffic.