Raindrop

Raindrop helps teams building AI agents find silent failures in production, investigate what went wrong using original traces as evidence, and test changes in CI or against real traffic. The page describes tracing every message, tool call, and decision; grouping recurring failures into issues; a Triage Agent that investigates and automates follow-ups in Slack, the web, or through MCP; signals and experiments to measure behavior changes; Workshop for local inspection and replay; and Simulations for testing agents before release. The page also lists SOC 2 compliance, PII redaction, SSO, audit logs, and a self-hosting beta, along with Hobby, Pro, and Enterprise plans.

Key features

• Tracing of every message, tool call, and run
• Issue detection that groups recurring failures across runs
• Root-cause investigation with original traces as evidence
• Triage Agent for investigation and follow-ups in Slack, web, or MCP
• Signals for custom behavior classifiers
• Experiments to compare changes against a baseline, including behind feature flags
• Workshop for inspecting, replaying, and debugging agents locally
• Simulations for testing agent changes, shown with pull request results
• MCP integration for connecting tools and running auto-fix loops
• Server-side PII redaction
• SOC 2 Type II compliance per the page
• SSO, audit logs, and access controls on Enterprise
• Self-hosting in beta

Best suited for

• Teams building and shipping AI agents
• Teams monitoring production agent failures
• Teams that want to verify agent fixes against real traffic before rollout

Pricing

Hobby: $0/mo with 1,000 events/mo included. Pro: $299/mo plus $0.003 per event up to 1M, then $0.002 per event, with a 14-day free trial. Enterprise: custom pricing.