Mirrors
The right context. At the right time.
Mirrors is a context-routing layer for AI agents that learns from recorded sessions to deliver guidance when it is relevant. It analyzes successes, retries, and customer corrections to identify patterns, then routes matching context as a conversation unfolds, aiming to prevent recurring mistakes from reaching customers.
The platform lets users write and preview guidance, edit tool descriptions, input schemas, and model-facing tool results before activation. Routing conditions can be tested against stored traces to review matching, missed, and unexpected sessions. Routing decisions run locally without network requests or model inference. Mirrors integrates with frameworks and tools including LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Pydantic AI, smolagents, Google ADK, Mastra, OpenAI, Anthropic, MCP, Claude Code, Codex, Cursor, and Windsurf. Outcome comparisons against holdout groups help measure whether context changes improve results.
Mirrors is aimed at teams building and maintaining AI agents who want to improve behavior using their existing traces and feedback. Onboarding starts with one workflow and exported traces, with pricing discussed for the specific use case.
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