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Control autonomous AI agents with policies, approval gates, and audit trails.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "cordum" yet — see the docs or source repo.
I am building an AI agent with LangChain that executes tasks automatically. Explain how to integrate cordum to add pre-execution approval gates, policy checks, and action auditing for high-risk operations, and provide an implementation checklist.
An integration plan explaining how to define high-risk actions, configure approvals, enforce policy blocking, and record audit logs.
Design a set of cordum policies for an AI agent connected to an internal knowledge base and external APIs. Restrict sensitive data exfiltration, block dangerous commands, and separate actions that can run automatically from those requiring human approval.
A clear draft of policy rules including risk levels, restrictions, approval criteria, and exception-handling guidance.
We need to review the past week of execution behavior in a CrewAI multi-agent system. Explain how to use cordum's audit trail capabilities to organize agent action records and identify blocked events, human approvals, and abnormal call paths.
An audit analysis approach that helps the team summarize agent activity, trace key decisions, and uncover potential risk points.
Detects agent infinite loops and provides safeguards with recovery recommendations.
Use multi-agent chat and multiple models to handle complex workflows.
Manage projects, tasks, decisions, knowledge, and handoffs for AI agents.
Orchestrate intelligent AI workflows with memory, integrations, and unified usage credits.
Turn compatible LLMs into CrewAI orchestrators for building and running multi-agent workflows.
Run deterministic agent orchestration with task decomposition, subagents, and review feedback.