Raindrop

Raindrop helps teams detect problems with AI Agents and prevent those problems from happening again. Its official positioning is: track every run, automatically fix silent failures, and run simulations before launch. The target users include teams that deliver Agents to massive numbers of users, from local testing to enterprise-grade deployment.

Main capabilities

• Tracing and localization: follow every message and every tool call to see exactly where a run goes wrong.
• Pattern grouping: discover the same failure pattern across multiple runs and group recurring problems into the same issue.
• Root cause analysis: use raw traces as evidence to trace back to the root cause of the problem.
• Pre-launch validation: view simulation results on pull requests and catch regressions before merging; compare changes against real traffic to determine which behaviors have improved.
• Alerts and automation: receive alerts immediately when production behavior goes off track; investigate problems in Slack, on the Web, or via MCP and automate follow-up; after connecting existing tools, Raindrop can run automated fix loops for Agents.
• Custom classifiers: define custom classifiers for the behaviors that truly matter, such as the official examples of "Aesthetic Complaints" and the refund_agent loop.
• Feature flag validation: when controlled by a feature flag, first prove that the improvement works before gradually rolling it out.

Typical problem examples given officially

• Build failure retry loop: the Agent repeatedly retries the build after restoring the same deprecated configuration key (such as module.loaders, which Webpack 5 no longer supports), reproducing the same error each time; it should switch to module.rules, update the shared template, and then replay the failed traces against that change.
• Duplicate refund execution: the refund itself succeeds, but the response times out, a new retry initiates another refund, and the Agent still replies that the refund has been issued.

How to use and integrate

• Start for free, no credit card required to begin tracing.
• An SDK is provided, and official user feedback mentions "with this new SDK, page us when something goes wrong."
• Supports Slack notifications and MCP as well as the Query SDK, allowing investigation and automated follow-up in Slack, on the Web, or via MCP.
• Supports simulating changes in CI and displaying the results in pull request.
• Supports validating improvements first through feature flags, then gradually rolling them out.
• Supports instrumenting local Agent work; official user feedback mentions it can be used for Claude Code sessions to improve skills, and can also be used for voice Agents.

Use cases

• Finding silent failures in production environments, locating the point of failure, and investigating.
• Viewing and sorting traces under multi-Agent, parallel workflows.
• Behavior-based monitoring and alerting, such as errors, user feedback patterns (for example, frequent regeneration, spikes in thumbs-down, and other custom failure conditions).
• Validating the effect of changes against real traffic and catching regressions before merging.
• Needing insights by user group, for example, official feedback mentions using Deep Search to build a "user speaks Chinese" classifier for the Chinese user group, which Raindrop will translate.

Pricing and plans (from the official page)

• Hobby: free, includes 1,000 events per month; includes tracing and search, Slack notifications, MCP and Query SDK, 14-day data retention, 1 custom signal, and 15 Agent messages per month. Official explanation: one event refers to one user message and Agent response, including tool calls and sub-Agents, or one background Agent run.
• Pro: builds on Hobby with real-time issue detection, a triage Agent for investigating failures, Edge-PII redaction (add-on), experiments, and semantic search; 500 Agent messages per month, 10 custom signals, unlimited data retention; overage is $0.003 per event (up to 1 million), then $0.002 per event thereafter.
• Enterprise: builds on Pro with SSO / SAML and audit logs, priority support and SLA guarantees, Snowflake / BigQuery export, unlimited Agent messages, unlimited custom signals; pricing is customized by team. Contact the official team if you need custom deployment.

Security and compliance Officially described as "Security trusted by the Fortune 100," and provides: SOC 2 Type II compliance, audited annually by an independent third party, with the full report available in its Trust Center; provides intelligent server-side PII redaction to protectsensitive user data; enterprise-grade capabilities include SSO, audit logs, access control, procurement support, and dedicated implementation assistance; Self-Hosting Beta supports running Raindrop in your own cloud environment.

Limitations and information not yet provided

• Apart from the above plan prices and billing units, pricing in other regions, taxes, refund policies, etc. are not yet provided.
• Performance parameters such as the context length of specific models, latency metrics, and the list of supported languages are not yet provided.
• The full list of third-party integrations, the supported languages and version requirements of the SDK are not yet provided.
• The official page mentions user feedback on using it with a Codex subscription and the in-app browser of the Codex desktop app, but does not provide an official support matrix; specific compatibility is subject to the official documentation.

Overall, Raindrop connects "discovering silent failures — clustering issue patterns — tracing root causes — pre-launch simulation validation — automatic fixes" into a closed loop, and adapts to the Agent behaviors that different teams care about through customizable signals and classifiers.