Raindrop

Raindrop is a monitoring platform tailored for AI agents, designed to detect and diagnose silent failures that traditional tools miss. It captures every agent run, including messages, tool calls, retries, and errors, providing a clear view of agent behavior and performance. The platform automatically surfaces issues like hallucinations, loops, and broken tools, alerting teams promptly to maintain reliability.

The tool targets AI developers, product managers, and engineering teams working with AI agents, from startups to enterprises. It supports local testing and large-scale deployments, helping teams understand user impact and root causes through detailed trace visualizations and natural language search.

Raindrop’s value lies in its ability to turn complex AI agent data into actionable insights. It offers features like custom signals to track specific behaviors, semantic search to find issues quickly, and experiments to A/B test agent changes. The platform integrates deeply with Slack, allowing users to interact with a Triage Agent that investigates problems conversationally and schedules regular reports.

Key differentiators include its self-healing capabilities where coding agents can automatically fix detected issues, and its MCP server that connects Raindrop data directly to coding assistants like Claude Code and Codex. This integration streamlines the debugging and deployment process without leaving the developer’s environment.

Technically, Raindrop supports multiple SDKs (TypeScript, Python, Go, Rust, Java) and offers a REST API, making integration flexible. It emphasizes security with SOC 2 compliance, PII redaction, and enterprise features like SSO and audit logs. A self-hosting beta is also available for organizations with strict deployment requirements.

Overall, Raindrop helps teams monitor AI agents effectively, detect subtle failures, and validate fixes through experiments, improving AI product quality and user experience.