Raindrop

What is Raindrop?

Raindrop is the first monitoring platform built specifically for AI agents in production. It solves the critical problem of silent failures that traditional monitoring tools miss—when AI agents hallucinate, loop endlessly, or break tools without triggering standard error alerts. Raindrop captures every agent run including messages, tool calls, retries, and errors, then uses custom models to detect real failures like hallucinations and loops. The platform lives in Slack, allowing engineers to triage issues, ask questions about their data, and prove fixes worked through live experiments. Trusted by Fortune 100 companies and fast-growing AI startups like Replit, Speak, and Clay, Raindrop processes billions of traces monthly.

Key Features

• Complete Agent Tracing

  Logs every production run capturing messages, tool calls, retries, and errors in one place, providing full visibility into agent trajectories and decision sequences.

• Automatic Issue Detection

  AI agents work in the background to triage and investigate potential issue patterns, generating step-by-step explanations of what happened when problems like hallucinations or tool failures emerge.

• Custom Signals & Classifiers

  Define custom signals for behaviors that matter to your product—beyond default signals like 'User Frustration,' teams can track 'Agent Stuck in a Loop' or 'UI Aesthetic Complaints' with incident rates over millions of events.

• Slack-Native Triage Agent

  Just @Raindrop in any Slack channel to ask questions, triage issues, create signals, and summarize biggest issues without leaving Slack. Keeps context across follow-ups and supports automated briefs.

• Experiments & A/B Testing

  The first A/B testing framework for AI agents that lets you prove improvements behind feature flags before rolling out, running experiments against live traffic to confirm regressions are gone.

• SOC 2 Compliant & Enterprise Ready

  SOC 2 Type II compliant with intelligent server-side PII redaction, SSO/SAML login, audit logs, access controls, and self-hosting beta for deployment in your own cloud.

Use Cases

• Production Agent Monitoring : AI engineering teams monitor deployed agents in real-time, getting Slack alerts when agents fail silently due to hallucinations, loops, or broken tools before users notice.
• Debugging & Root Cause Analysis : Engineers investigate complex agent issues by diving into traces and tool calls to find root causes, with the Triage agent providing step-by-step explanations of what went wrong.
• Validating Agent Fixes : After shipping fixes, teams run experiments against live traffic with feature flags to confirm regressions are permanently resolved, not just temporarily patched.
• Custom Behavior Tracking : Companies in healthcare, financial services, and education track domain-specific signals like 'toxic user behavior' or 'compliance violations' that matter to their business.
• Multi-Agent Workflow Observability : Teams building parallel or multi-agent workflows use Raindrop to tame 'trace spaghetti,' sorting through complex trajectories to discover which agent caused issues.

FAQs