Raindrop provides an observability platform for AI agents that captures every interaction through lightweight SDKs and no‑code connectors. It delivers real‑time alerts, step‑by‑step execution tracing, AI‑driven classifiers, and searchable logs to help engineers detect silent failures, tool‑call anomalies, and user‑frustration, while offering enterprise‑grade security and compliance.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents deployed in production often fail silently, generate unexpected tool calls, or produce degraded user experiences that are hard to detect without extensive manual logging. Engineers lack a unified view of agent behavior, making it difficult to pinpoint abnormal execution paths, quantify user frustration, or verify the impact of model updates. This opacity leads to delayed issue resolution, higher churn, and wasted engineering cycles.
Solution
Raindrop delivers a Sentry‑style observability platform built specifically for AI agents. It ingests every interaction, enriches events with metadata, and runs AI‑powered classifiers to surface silent failures, tool‑call anomalies, and user‑frustration signals in real time. Engineers can define custom issue types, trace execution step‑by‑step, and receive instant Slack or webhook alerts tied to the underlying event payload. The platform offers semantic and regex‑based search across millions of events, enabling rapid root‑cause analysis and continuous A/B testing of prompts, models, and feature flags. All data is stored with enterprise‑grade security, including PII redaction and SOC 2 Type II compliance, while SDKs for Python, Node, and no‑code Segment integration keep instrumentation to two lines of code.
Target Audience
The primary customers are AI product teams that build conversational agents, autonomous assistants, or tool‑augmented bots—ranging from consumer AI apps to enterprise workflow automation platforms. It serves engineers, data scientists, and reliability engineers who need production‑grade visibility into agent behavior.
Features
- SDKs and no‑code connectors that capture every agent turn with a two‑line integration
- Real‑time alerting (Slack, webhook, email) with direct links to the offending trace
- Custom issue definitions and step‑by‑step execution tracing for deterministic debugging
- AI‑driven classifiers for user frustration, tool‑call failures, and abnormal trajectory detection
- Regex and deep semantic search across all logged events, supporting fast root‑cause queries
- Built‑in experimentation framework for A/B testing prompts, models, and feature flags
- Enterprise security suite: PII Guard redaction, SOC 2 Type II compliance, SSO and role‑based access
- Topic clustering and automatic issue detection to surface emerging patterns without manual effort