DashClaw and Aegis
These are **competitors** offering overlapping core functionality—both provide policy enforcement and audit trails for agent actions—though DashClaw emphasizes decision infrastructure while Aegis emphasizes runtime enforcement with cryptographic guarantees.
About DashClaw
ucsandman/DashClaw
🛡️Decision infrastructure for AI agents. Intercept actions, enforce guard policies, require approvals, and produce audit-ready decision trails.
Sits as a middleware layer between agents and external systems, evaluating declarative guard policies with pre-execution interception. Supports multiple SDKs (Node.js/Python), framework integrations (LangChain, CrewAI, Claude Code, OpenAI Agents SDK), and includes real-time approval queues with behavioral drift detection via statistical analysis of agent assumptions.
About Aegis
Justin0504/Aegis
Runtime policy enforcement for AI agents. Cryptographic audit trail, human-in-the-loop approvals, kill switch. Zero code changes.
Intercepts tool calls at the gateway level using SDK auto-instrumentation, HTTP proxying, or MCP integration, classifying them against zero-config detectors (SQL keywords, path traversal, prompt injection patterns) before execution. Stores tamper-evident records via SHA-256 hash chaining with optional cryptographic signing, while offering human-in-the-loop approval workflows where high-risk calls pause and route to a web dashboard for manual decision-making.
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