Trajeckt is a platform designed to enforce runtime policies and provide observability for AI agent operations. It addresses the challenge of managing sequences of actions by AI agents, focusing on ensuring that entire trajectories—not just individual tool calls—comply with declared plans. The platform operates below the model layer, intercepting actions before any irreversible step is taken, and blocks actions that deviate from the allowed sequence or require human approval.
Key features of Trajeckt include trajectory-based enforcement, where each tool call is checked against a declared plan before execution, and the position within the sequence determines whether an action is allowed or blocked. The system generates a structured evidence layer for every execution, offering live feeds, policy state, replay history, and learning signals to help users understand and improve agent behavior. Users can investigate past runs through replay functionality, tracing every decision and outcome without relying on raw logs. The platform also provides benchmarking capabilities, with performance metrics tied to real benchmark runs.
Trajeckt integrates as a gateway, not a library, and is compatible with agent stacks that use MCP or OpenAI-compatible tool calls. Integration requires only a configuration change, and the platform supports connections with tools and frameworks such as MCP, Claude Agent SDK, LangChain, LangGraph, and OpenAI SDK. The service offers a control surface for agent observability, governance, and investigation, including analytics on trajectories, human approvals, incident replay, and real-time cluster status. Actions can be exported as JSON records, and the system is designed to add minimal latency (less than 3ms p95) to agent operations.
A free trial is available for new users. The platform targets teams or individuals responsible for operating and overseeing AI agents, providing tools to ensure compliance, auditability, and operational intelligence. Trajeckt is positioned as an enforcement and observability solution for AI agent workflows, emphasizing trajectory-level control and investigation.
Trajeckt is a LLM eval & observability product. It focuses on preventing AI agents from executing unintended or unsafe actions by enforcing runtime policies and observability. It is built as a B2B product for AI operations teams. It runs on the web and API.
Behind Trajeckt is Tamor AI, and the product first shipped in 2026. Key capabilities include runtime enforcement, policy management, and live feeds. It exposes integrations via a public API.
Latest indexed changes and source events
Trajeckt: a fail-closed gateway that enforces what AI agents can do (~1.6ms) verified by the PulseGate indexer
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