Compile context
Stop agents from acting on the wrong context.
Prepare the files, documentation, policies, tickets, and task history relevant to the task.
Coreledger Technologies
Control what developer agents see, do, and prove.
Contextus is our flagship product, the control layer between developer agents and the tools they use.
Prepare the right context, apply policy before consequential actions, require approval when risk rises, and keep a reviewable record of what happened.
AI engineering teams • Platform teams • Developer-tool teams
Flagship product
Contextus
Your agent does the work. Contextus controls the boundaries.
Contextus sits between developer agents and the tools they use, adding context control, policy, approvals, identity, and evidence without forcing teams to replace their existing workflows.
See how Contextus worksClaude CodeCursorCodexMCPYour agent
Contextus
Context • Identity • Policy • Risk • Approval • Proof
Files
Commands
APIs
Data
Infrastructure
Compile context → Govern actions → Approve risk → Prove outcomes
Why now
Agents have moved from answering questions to taking actions.
Developer agents can edit repositories, run commands, install packages, call APIs, use credentials, and affect production-adjacent systems.
That changes the problem.
It is no longer only: Can the agent complete the task?
Teams also need to know
- Did it have the right context?
- Was it authorized to take the action?
- Did the action require review?
- Who approved it?
- What happened afterward?
Contextus is designed around those questions.
How Contextus helps
One control loop around agent actions.
Govern actions
Check consequential actions before they reach real systems.
Apply policy to tools, commands, APIs, data, model choices, and requested actions.
Approve risk
Put humans in the loop when the action warrants it.
Safe work can continue while higher-risk actions pause for authorized review.
Prove outcomes
Know why an action was allowed or blocked.
Keep the agent, policy decision, reviewer, rationale, and outcome together.
Built for teams deploying agents
For teams moving agents from demos into real workflows.
AI engineering teams
Build agent workflows with reliable context, policy controls, evaluations, and review paths.
Platform teams
Define shared policies, approval paths, agent authority, and evidence requirements.
Developer-tool teams
Add governed agent actions to IDEs, MCP servers, CI workflows, and internal automation.
Coreledger Technologies
Built around the realities of production systems.
Coreledger Technologies develops AI infrastructure for controlled, reviewable agent workflows.
Our experience with reliability, reconciliation, data systems, and production engineering shaped a simple view of AI agents: as they gain more ability to act, the systems around them need clearer context, stronger boundaries, and better evidence.
Contextus is built around that idea.
Explore Coreledger
Research and ideas behind the products.
Lab
Research, prototypes, and experiments around context, agent systems, and applied AI.
Explore the LabWriting
Technical perspectives on agent control, context engineering, identity, routing, and production AI.
Read our writingPodcast
Conversations about technology, engineering, product building, and what survives contact with production.
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Start with one governed agent workflow.
Keep the agent and tools you already use. Add control around the actions that matter.