Company Description

Multi-agent systems fail quietly today due to state drift, broken assumptions, and coordination breakdowns. Arzule ingests failed traces from tools like CrewAI, LangChain, Claude Code, and custom stacks, finds coordination failures, and generates a corrected trace. Users can approve or deny the correction so Arzule learns what “good” looks like in the context of the current project. It provides observability, debugging tools, failure detection, and patch plans that can be dropped back into agent workflows to improve costs, efficiency, and quality. Additionally, Arzule is currently offering early access to synthetic creation and labeling of multi-agent coordination tasks for companies who reach out.