Laminar records 0 monthly visits with 0% month-over-month growth and Freemium pricing. Raindrop records 42,807 monthly visits with -18.4% growth and Free Trial, Paid, Contact for Pricing pricing.
Open-source agent observability that catches failures before your users do
Find and fix problems in your AI agents before users do
| Dimension / Metric | | |
|---|---|---|
| Official Domain | lmnr.ai | raindrop.ai |
| Pricing Model | Freemium | Free Trial, Paid, Contact for Pricing |
| Monthly Visits | 0 (0) | 42.81K (42,807) |
| MoM Traffic Delta | 0 (0%) | -9.63K (-18.4%) |
| Primary Market & Share | 🌐 Global (—) | 🇺🇸 United States (77.1%) |
| Direct Visits / mo | 0 | 23.55K |
| User Rating | 4.7 | 4.4 |
| Supported Platforms | Website | Website |
Open-source agent observability that catches failures before your users do
Automatically records LLM calls, tool calls, sub-agents, tokens and cost, then shows them as a readable transcript with a cost heatmap.
A custom analysis model reviews every run to surface failure modes you never defined, then clusters similar failures into patterns for fast triage.
Convert error clusters into eval datasets and re-run them after each release to catch regressions before they reach users.
Get notified about new failure clusters in Slack and ask the Laminar agent questions about your traces from the same channel.
Find and fix problems in your AI agents before users do
See every message, tool call and decision in a run, with inputs, outputs and durations, so you can pinpoint where a run broke down.
Recurring failures are grouped into issues with severity, affected users, last-seen time and a confidence score, instead of scattered alerts.
An agent investigates issues and automates follow-up across Slack, the web app and MCP, so debugging happens where your team already works.
Run scenarios against a change on a pull request and compare results with real traffic to catch regressions before merge.
SpecialistUnified observability, security and incident response for cloud-scale engineering teams
SpecialistUnified observability, security and incident response for cloud-scale engineering teams
Track, evaluate, and ship AI models and agents in one connected environment.
Track, evaluate, and ship AI models and agents in one connected environment.
Free / Open-sourceAgent observability, evaluation, and continuous improvement for production AI
Free / Open-sourceAgent observability, evaluation, and continuous improvement for production AI
Free / Open-sourceBuild, simulate, evaluate and monitor self-improving AI agents
Free / Open-sourceBuild, simulate, evaluate and monitor self-improving AI agents
Free / Open-sourceEvaluate, monitor, and govern your AI applications in production
Free / Open-sourceEvaluate, monitor, and govern your AI applications in production
SpecialistThe collaboration layer for AI engineering teams
SpecialistThe collaboration layer for AI engineering teams
Standardize LLM evaluation, observability, and red teaming across your whole org
Standardize LLM evaluation, observability, and red teaming across your whole org
Automated QA, simulation and observability for voice and chat AI agents
Free / Open-sourceOpen-source observability that finds your AI agent's failures — and fixes them
Free / Open-sourceOpen-source observability that finds your AI agent's failures — and fixes them
Full-stack observability with an AI SRE agent that fixes issues
Full-stack observability with an AI SRE agent that fixes issues
Observe, evaluate and monitor AI agents in production
Observe, evaluate and monitor AI agents in production
Free / Open-sourceOpen-source observability that turns AI agent production failures into tested fixes
Free / Open-sourceOpen-source observability that turns AI agent production failures into tested fixes
