Laminar
Laminar is an open-source observability platform for AI agents, providing trace viewing, AI-powered failure detection (Signals), step-level debugging, and regression evals. It serves AI agent developers and enterprises deploying agents at scale, with native integrations across 15+ AI frameworks.
- Company typePrivate
- Founded2024
- HeadquartersSan Francisco, United States
- Headcount1–10
- GTM typeB2B
- OfferingSoftware
What Laminar does
Laminar is a San Francisco-based software company, founded in 2024 by Robert Kim and Dinmukhamed Mailibay, that builds an open-source observability platform purpose-built for AI agents. The platform captures detailed agent activity — including LLM reasoning, tool calls, sub-agent invocations, and input/output data — and exposes it through a navigable trace transcript, timeline, and AI-powered Q&A interface (TraceChat). Adjacent modules include Signals for natural-language-driven failure detection and Slack alerting, a True Agent Debugger that lets developers replay agent runs from any step, an Evals framework that converts error clusters into regression test datasets, Custom Dashboards with full SQL access, screen recording for browser agents, and full-text search across every span. The platform integrates natively with 15+ AI agent frameworks, including Anthropic's Claude Agent SDK, OpenAI's Agents SDK, Vercel AI SDK, LangChain, LiteLLM, Pydantic AI, Mastra, Browser Use, Stagehand, Playwright, and OpenHands SDK, and is differentiated by claimed 20x more efficient storage compression and a 5% instrumentation overhead versus competitors LangSmith (0%), AgentOps (12%), and Langfuse (15%).
The business model is a freemium open-source architecture licensed under Apache 2.0, with a free tier for self-serve sign-ups, paid cloud hosting subscriptions, and enterprise contracts for self-hosted deployments with HIPAA and SOC 2 Type II compliance. Go-to-market combines product-led growth through GitHub and a Discord developer community, community-led adoption via Y Combinator, and enterprise field sales behind a 'Book a demo' CTA. The company has raised approximately $3.5M in total funding across a $500K Y Combinator pre-seed (September 2024) and a $3M seed round led by Atlantic.vc (March 2026), and recently appointed Sanjay Rajan as Chief Revenue Officer to build out global sales and marketing. The publicly named reference customer is Browser Use, whose CEO Magnus Müller is quoted on the company homepage running 'millions of agent sessions' through the platform.
Laminar firmographics
Firmographics- Name
- Laminar
- Legal name
- Laminar
- Website
- https://lmnr.ai
- Company type
- Private
- Founded year
- 2024
- Operating status
- Operating
- Headcount range
- 1–10 employees
- Short description
- Laminar is an open-source observability platform for AI agents, providing trace viewing, AI-powered failure detection (Signals), step-level debugging, and regression evals. It serves AI agent developers and enterprises deploying agents at scale, with native integrations across 15+ AI frameworks.
- Ownership category
- akta.pro rank
Laminar industry classification
Industry- Product category
- AI Agent Observability Platform
- NAICS
- Software Publishers (513210), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (5182)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management) (HDAEANAA)
- akta.pro secondary industries
- Model Deployment, Serving & Inference Platforms (HDAAABAF), Responsible AI, Security & Privacy Platforms (Safety, Guardrails, PII) (HDAEANAG), Model Hosting, Serving & Inference Platforms (HDAAACAB)
Keywords
Where Laminar is headquartered
LocationHeadquarters
- HQ city
- San Francisco
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
Laminar business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Infrastructure, Operations, Marketing or Sales
Revenue model
- Open Source Platform: Core platform is fully open source under Apache 2.0 license, allowing free self-hosting. Revenue model likely includes paid cloud hosting, enterprise features, and support services.
- Enterprise Cloud Hosting: Cloud-hosted platform with enterprise-ready features including HIPAA compliance, SOC 2 Type II certification, and PII redaction at scale.
- Enterprise Self-Hosting: Self-hosted deployment options with full features for enterprise customers requiring data control, available via Docker or Helm charts on AWS/GCP.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Monthly | Free tier for individual developers and small teams |
Go-to-market motion3 records
Distribution channels4 records
Marketing channels7 records
Laminar product offering
Product offeringCore offering
Laminar provides an open-source observability platform for AI agents that captures detailed agent activity including LLM reasoning, tool calls, and sub-agents. The platform enables developers to replay failed agent runs from specific steps, detect failure patterns via natural-language queries, run regression evals, and visualize traces, with optional cloud-hosted and self-hosted deployments.
Product overview
Laminar is an open-source observability platform for AI agents, offered as a unified platform with multiple integrated modules. The core platform provides trace viewing (Trace/TraceChat) for navigating agent runs with transcript and timeline views, Signals for automated failure detection via natural language queries, and a Debugger for iterative agent development with Claude integration. Supporting modules include Evals for regression testing, Custom Dashboards and SQL Editor for data analysis, Screen Recording for browser agent visual context, and Full-Text Search across all trace data. The platform integrates natively with major AI frameworks (Claude Agent SDK, Vercel AI SDK, OpenAI Agents SDK, LangChain, LiteLLM, Pydantic AI, Mastra, Browser Use, Stagehand, Playwright) and supports self-hosting via Docker or Helm charts on AWS/GCP with enterprise-ready features including HIPAA and SOC 2 Type II compliance.
Differentiator
Problem solved
Functional benefit
Products and services
- Laminar Observability Platform Open-source, self-hostable platform providing end-to-end observability, debugging, evaluation, and chain management for AI agents, with integrations to 15+ AI frameworks.
- Trace and TraceChat Interactive trace viewer that exposes input, LLM reasoning, tool calls, sub-agents, timeline, and cost heatmap, with an Ask AI chat interface for natural-language querying of runs.
- Signals AI-powered alerting system that uses plain-English descriptions to identify failure patterns across every agent run, groups events into named clusters, and tracks each cluster over time with automatic resolution and reopening.
- True Agent Debugger Step-level agent debugger that lets developers replay failed runs from any step without restarting, with CLI and Model Context Protocol integrations enabling coding agents to run, read, fix, and re-run agents with cached state.
- Evals Evaluation framework that automatically converts fixed error clusters into eval datasets and runs regression evals after code or model changes, with per-model scoring, status, and duration tracking.
- Custom Dashboards and SQL Editor SQL-based dashboarding and full SQL access to all platform data, enabling custom analytics on traces, signals, and metrics, queryable by humans and coding agents via MCP or CLI.
Quantifiable outcome
- 20x cheaper storage compared to alternatives
- +1 more outcomes
Companies that use Laminar
Customer profileNamed customers2 records
Segments2 records
Ideal customer profiles2 records
Laminar technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration15 records
AI capability8 records
Feature9 records
Laminar partnerships and signals
Strategic signalPartnerships
Eight partnerships are on record, tiered core.
- Claude Agent SDK (Anthropic)coreLaminar provides native integration with Anthropic's Claude Agent SDK, enabling comprehensive observability and tracing for agents built with Claude.
- OpenAI Agents SDKcoreLaminar integrates with OpenAI's Agents SDK, providing observability capabilities for agents built using OpenAI's framework.
- Vercel AI SDKcoreLaminar integrates with Vercel's AI SDK for observability of AI applications built on the Vercel platform.
- LangChaincoreLaminar provides integration with LangChain, one of the most popular frameworks for building LLM applications.
- LiteLLMcoreLaminar integrates with LiteLLM, enabling observability for applications using LiteLLM's unified interface for multiple LLM providers.
- Browser UsecoreLaminar integrates with Browser Use for browser automation agent observability, including screen recording capabilities.
- Anthropic SDKcoreLaminar integrates with Anthropic's SDK for comprehensive observability of Claude-based applications.
- OpenAI SDKcoreLaminar integrates with OpenAI's SDK for observability of GPT-based applications.
Scale indicators2 records
Recent moves6 records
Expansion highlights6 records
Laminar competitors and assessment
Company assessmentDirect peers
- LangSmith: LangChain's native LLM/agent observability and evaluation platform. Direct competitor with deep LangChain integration, the largest agent-framework user base, and first-party default status that Laminar explicitly benchmarks against.
- Langfuse: Open-source LLM application observability, tracing, and evaluation platform with self-hosting. Closest direct peer in product scope (tracing, evals, prompt management) and business model (open source + managed cloud), and a primary benchmark for Laminar's pricing and overhead claims.
- Helicone: Open-source LLM observability and monitoring platform offering tracing, cost tracking, and caching for AI applications. Directly comparable in target customer (LLM/agent developers) and freemium open-source positioning.
- AgentOps: AI agent observability and evaluation platform explicitly benchmarked against Laminar (cited at 12% instrumentation overhead). Competes for the same agent-developer persona with tracing, eval, and debugging features.
- Arize AI: LLM and ML observability platform with tracing, evaluation, and drift monitoring. Broader in scope than Laminar but addresses the same agent/ML production-monitoring use case with enterprise sales motion.
Broad incumbents
- Datadog: Large-scale APM and observability incumbent with LLM/AI monitoring via Datadog LLM Observability. Not agent-specialized but has the enterprise GTM, scale, and infrastructure to absorb agent observability workloads as a feature within a broader platform.
- Honeycomb.io: Observability platform focused on high-cardinality traces for production systems. Adjacent in tracing technology and developer persona but not LLM/agent-specialized; relevant as a potential acquirer or strategic competitor.
- Sentry: Application monitoring and error tracking platform with growing AI/LLM integrations. Targets the same developer persona for production debugging but with a much broader, more mature platform and significantly larger user base.
- Weights & Biases: ML experiment tracking, model evaluation, and observability platform with established enterprise adoption. Adjacent to Laminar on the eval/regression-testing axis and on the ML/AI production monitoring use case.
Emerging players
- Maxim AI: Emerging AI evaluation, observability, and simulation platform targeting teams building production AI agents and applications. Early-stage peer focused on the same developer persona, with overlapping tracing and eval feature set.
Market position
Strengths3 records
Weaknesses5 records
Competitive moat5 records
Key risks6 records
Key highlights7 records
Customer concentration
Laminar social profiles
Digital presenceLaminar compliance and trust
Trust signalCompliance3 records
Laminar financial estimates
Financial estimateRevenue estimate
Valuation estimate
Laminar leadership team
Management profileNumber of profiles
Profiles3 records
Laminar funding detail
Funding detailFunding overview
Funding rounds2 records
Investors3 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Laminar M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Laminar
What does Laminar do?
Laminar provides an open-source observability platform for AI agents that captures detailed agent activity including LLM reasoning, tool calls, and sub-agents. The platform enables developers to replay failed agent runs from specific steps, detect failure patterns via natural-language queries, run regression evals, and visualize traces, with optional cloud-hosted and self-hosted deployments.
Is Laminar a public or private company?
Laminar is a private company. It is classified as venture growth investor backed and is currently operating.
When was Laminar founded?
Laminar was founded in 2024. It employs 1 to 10 people.
Where is Laminar based?
Laminar is headquartered in San Francisco, United States, in the North America region.
How does Laminar make money?
Three revenue lines are on record. Open Source Platform is the primary driver. The others are enterprise Cloud Hosting and enterprise Self-Hosting.
Who are Laminar's main competitors?
Direct peers on record are LangSmith, Langfuse, Helicone, AgentOps and Arize AI. Broad incumbents are Datadog, Honeycomb.io, Sentry and Weights & Biases. Maxim AI is listed as an emerging player.
Does Laminar have an API?
Yes. Laminar provides multiple programmatic interfaces: (1) CLI tool for platform interaction and debugger sessions, (2) MCP (Model Context Protocol) server enabling coding agents to query traces, fix issues, and re-run with cached state directly from the Debugger session UI, (3) Full SQL access to all platform data with ability for coding agents to query via MCP or CLI, and (4) Full-text search across every span input, output, and attribute.
What industry is Laminar in?
Laminar's product category is AI Agent Observability Platform. Its primary akta.pro industry code is HDAEANAA, End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management), with a secondary code of HDAAABAF, Model Deployment, Serving & Inference Platforms. Its NAICS code is 513210 and its SIC code is 7372.