Raindrop

Raindrop is a monitoring and observability platform for AI agents in production that detects silent failures such as hallucinations, tool misuse, forgotten context and user frustration, which error trackers and offline evals miss. It is built for engineering teams shipping customer-facing agents who need to know when behavior regresses, why it happened, and whether a fix actually works.

Raindrop is a production monitoring and observability platform for AI agents, built by a San Francisco team from Y Combinator's Winter 2024 batch that positions the product as 'Sentry for AI agents.' Instead of relying only on offline evals, Raindrop ingests live agent traces through TypeScript and Python SDKs or an HTTP API and flags semantic failures that conventional APM misses: an agent confidently giving wrong answers, forgetting earlier context, refusing tasks, misusing tools, or leaving users visibly frustrated. It combines explicit signals such as thumbs-up/down, regenerations and copy events with implicit signals detected by LLM-based binary classifiers, then trains lightweight models underneath so the approach scales to millions of events a day. Seven preset signals (user frustration, task failure, forgetting, refusals, jailbreaking, NSFW content and user praise) ship on every plan, and teams can define custom signals in plain English. Recurring patterns are grouped into Issues, investigated by a Triage Agent available in Slack, the web app or over MCP, and validated with Experiments that compare agent variants. In May 2026 the company released Workshop, a free open-source local debugger that streams traces to a browser and exposes them to Claude Code over MCP. On September 17, 2026 it announced a $35 million Series A led by CRV, bringing total funding to $50 million, alongside Simulations, an early-access product that replays real production traffic and existing test cases against proposed agent changes before they merge. Named customers include Vercel, Clay, Framer, Speak, AngelList and Browserbase, and the company says Fortune 100 enterprises in healthcare and logistics use it. It competes with LangSmith, Langfuse, Braintrust and Arize.

Category

Developer Tools

Pricing

Freemium, Subscription, Usage-based

Target Market

CTOs, VPs of Engineering, AI/ML Engineers, Product Managers

Deployment

Cloud-first, API-based

Founded

2023

Headquarters

San Francisco, USA

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  Semantic Signals

  Seven preset classifiers (frustration, task failure, forgetting, refusals, jailbreaks, NSFW, praise) plus custom signals written in plain English, so teams track behavioral failures rather than only latency and errors.

• ✓
  Issue Detection

  Groups recurring failure patterns across production runs into tracked issues with rates over time, surfacing regressions that no single trace or log search would reveal.

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  Agent Tracing

  Captures every message, tool call and decision in an agent trajectory, giving engineers the full context needed to reproduce and understand a failure.

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  Triage Agent

  An investigation agent available in Slack, the web app or as an MCP server that digs into failures and answers natural-language questions about production data.

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  Experiments

  Compares agent variants and feature-flagged changes against production signals so teams can prove a prompt or model change actually improved behavior for users.

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  Simulations (early access)

  Replays real production traffic and existing test cases against a proposed agent change, running anomaly detection to catch regressions, cost changes and output drift before merge.

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  Workshop local debugger

  Free open-source tool that streams agent traces to a local browser UI and exposes them to Claude Code over MCP so the coding agent can diagnose and fix issues.

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  PII Guard and enterprise controls

  Server-side PII redaction plus SAML SSO and audit logs on Enterprise let regulated teams send production conversations without exposing sensitive user data.

• •
  Catching silent regressions after a model swap

  A team upgrading its underlying LLM watches task-failure and frustration signal rates and spots a behavior regression within hours instead of from support tickets.

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  Debugging long-running tool-calling agents

  Engineers trace multi-step agent runs with many tool calls to pinpoint exactly where the agent misused a tool or lost earlier context.

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  Validating a prompt or model change before shipping

  Product teams use Experiments or Simulations to replay real traffic against a candidate change and confirm it improves outcomes before it reaches every user.

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  Monitoring consumer assistants for safety

  Trust-and-safety teams track jailbreak, NSFW and refusal signals across large conversation volumes to catch abuse attempts and over-refusal trends early.

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  Routing agent incidents into the on-call workflow

  On-call engineers receive Slack alerts about a new issue and ask the Triage Agent to summarize affected conversations and likely root causes before paging anyone else.

List pricing is published. Hobby is free but hard-capped at 1,000 events a month. Pro is $299/month plus $0.003 per event up to 1M and $0.002 after, with no events included in the base fee; an event is one agent turn (user input, the tools the agent ran, and the assistant output), so 100K turns list at about $599/month and 1M at about $3,299. SSO/SAML, audit logs, edge PII redaction, warehouse exports and SLAs require a custom-priced Enterprise contract.

This page was written from 10 sources, 6 on domains other than raindrop.ai.

1. 1.raindrop.ai — raindrop.aivendor
2. 2.raindrop.ai — plansvendor
3. 3.raindrop.ai — signalsvendor
4. 4.raindrop.ai — introducing workshopvendor
5. 5.thenextweb.com — raindrop series a 50m crv agent failures simulations
6. 6.runtimewire.com — raindrop raises 35m series a launches agent simulations
7. 7.ycombinator.com — raindrop
8. 8.zenml.io — production monitoring and issue discovery for ai agents
9. 9.hn.algolia.com — 45924712
10. 10.befailproof.ai — raindrop ai pricing