Raindrop

Raindrop is an observability and monitoring platform designed specifically for AI applications. It helps AI engineers and product teams detect hidden issues in LLM- and ML-powered products by turning raw interaction data into actionable insights. The primary purpose of Raindrop is to provide continuous visibility into how AI features behave in production, so teams can catch regressions early, improve reliability, and maintain user trust.

Raindrop ingests logs and traces from your AI app—such as prompts, model responses, metadata, and user feedback—and structures them into searchable, filterable events. It enables teams to define custom metrics and alerts around hallucinations, safety violations, latency spikes, prompt failures, and degraded answer quality. Raindrop supports evaluation workflows with automatic scoring using heuristics, LLM-based judges, or human labels, so teams can track quality over time and across model versions. It also provides cohort analysis and segmentation, helping you understand how performance varies by user segment, use case, or traffic source.