Home / Directory / AI SaaS tooling / Observability & monitoring / Raindrop
Raindrop
San Francisco company from Y Combinator's Winter 2024 batch that monitors AI agents in production, groups recurring failures into issues, and tests changes with simulations.
Product and engineering teams running AI agents with real users who need to find and fix failures that standard logging misses.
Teams with a single prototype and low traffic, or buyers who want prices with no per-event charges.
Verdict
Raindrop is a San Francisco company that monitors AI agents in production and shows teams where they fail users. It suits product and engineering teams running agents at scale that need to find silent failures and test fixes. Its founders built it after struggling to see their own agent failures.
Score Breakdown
How Raindrop scores in the categories that matter to its buyers.
Pricing
Raindrop publishes a free Hobby plan and a monthly Pro price with metered events, and sells Enterprise on custom terms.
| Plan | Price | What stands out |
|---|---|---|
| Hobby | Free | 1,000 events a month, 1 custom signal |
| Pro | $299 / month | Issue detection, experiments, memory; events metered from $0.003 each |
| Enterprise | Custom | SSO, PII redaction, audit logs, warehouse exports, SLAs |
The Field at a Glance
How Raindrop compares with other Observability & monitoring vendors we reviewed, by Overall Score and relative typical engagement cost.
Raindrop scores 7.9 in Observability & monitoring, under Fiddler AI (8.1), level with Langfuse (7.9), and ahead of Arize AI (7.7) and Evidently AI (6.8). Relative cost lands mid-band for this subcategory.
Use-case matrix
| Use case | Fit | Notes |
|---|---|---|
| Silent failure detection | Strong | Finds agents that skip tasks or call the wrong tools. |
| Issue grouping | Strong | Rolls recurring failures into one issue. |
| Simulations | Strong | Tests changes against real traffic before merge. |
| Enterprise controls | Strong | SSO, PII redaction, and audit logs on Enterprise. |
| Free tier | Mixed | Hobby stops at 1,000 events a month. |
| Metered events | Mixed | Pro bills extra events. |
Who it’s for
Good fit
- Teams running agents with real users
- Product managers tracking agent quality
- Engineering teams debugging agents
Poor fit
- Low-traffic prototypes
- Buyers wanting flat pricing
- Teams needing only token-cost dashboards
Review Excerpts
Below are excerpts from public reviews. Our team scoured public reviews, forums, and chat rooms to get a balanced view of customers' experience with this company. Paid reviews and pay-for-play sites such as Clutch were excluded.
Raindrop says it has moved from a tool loved by startups to one trusted by large enterprises in healthcare, logistics, and other industries.
Raindrop groups recurring agent failures across many runs into a single issue and links the original traces as evidence of the root cause.
Raindrop's free Hobby plan stops ingesting events for the month after 1,000, and issue detection and experiments require the $299 Pro plan.
Company Facts
- Founded
- 2023 (Y Combinator)
- Headquarters
- San Francisco (Y Combinator)
- Accelerator
- Y Combinator, Winter 2024 batch (Y Combinator)
- Seed funding
- $15M led by Lightspeed (Raindrop)
- Total funding raised
- $50M, with a Series A led by CRV, September 2026 (Raindrop)
- Founders
- Ben Hylak, Alexis Gauba, and Zubin Koticha (Y Combinator)
- Website
- raindrop.ai
Key Leadership
Ben Hylak
Co-founder
Methodology
This page is an independent evaluation of Raindrop for buyers comparing options in observability & monitoring. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. Raindrop did not pay for this review.
What we scored
The headline number is an Overall Score on a 0-10 scale. Eight criteria sit under it in two groups.
- Buyer outcomes (for observability & monitoring)
- Agent failure detection
- Investigation tools
- Free tier depth
- Enterprise readiness
- Company & commercial
- Innovation & product leadership
- Project management & communication
- Pricing
- Contract fairness
Pricing measures whether the price looks fair for the value delivered, including packaging and renewal friction that show up in real buying cycles.
Score Composition
| Input | Weight | What it covers |
|---|---|---|
| Reviews | 40% | A proprietary read of what practitioners say about likes, complaints, and day-to-day use, including public review sites, forums, and private chat rooms. Paid reviews and pay-for-play sites such as Clutch are out of scope. |
| Product | 35% | Hands-on look at screens and workflows. |
| Pricing | 15% | Whether the price looks fair for what you get. |
| Docs & training | 10% | Docs, tutorials, and training material. |
How we balanced the evidence
The Overall Score is the simple average of the eight criteria. Recommendation language follows that score and the fit pattern described above.
Scope
Raindrop is graded here as observability & monitoring. Criteria scores can move as more review volume and product checks are added.