Judgment Labs
Judgment Labs builds an Agent Behavior Monitoring platform that helps teams running production AI agents detect failures, evaluate trajectories, and continuously improve agent behavior from production data. Founded in 2025, based in San Francisco, it serves hundreds of teams including startups and DoorDash.
- Company typePrivate
- Founded2025
- HeadquartersSan Francisco, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
What Judgment Labs does
Judgment Labs operates a continuous-improvement stack for production AI agents, founded in 2025 and headquartered in San Francisco with a team of fewer than 20 people. The company's Agent Behavior Monitoring (ABM) platform ingests full agent trajectories at petabyte scale via ClickHouse, Kafka, Spark, Flink, and Ray pipelines — reportedly handling hundreds of thousands of traces per second — and surfaces behavioral failures, instruction drift, and context retrieval loss that are otherwise invisible in long-horizon, multi-step agent runs. Its four core modules are Agent Search (behavioral-level trajectory querying), Agent Judge (an agentic evaluation harness with Search, Verification, and Adaptation capabilities plus the Rubric Builder feedback loop), Behavior Discovery (failure-mode surfacing from unlabeled trajectories), and AutoRubrics (automatic rubric construction and refinement from production signals); the company also ships the Judgment MCP server, which embeds the product into Claude Code, Codex, and Cursor, and a Slack-native "Ask Judgment" interface for in-channel triage and alerting.
The platform is built around a multi-agent Reader/Worker/Forker evaluation architecture that verifies agent stateful actions against source-of-truth systems such as GitHub, AWS IAM, AWS Secrets Manager, AWS CloudWatch, and CRMs. Internally reported benchmarks place Agent Judge at 0.86 accuracy on trajectory-level hallucination detection after five Rubric Builder refinement iterations, ahead of Claude Code (0.73), Codex (0.69), and a GPT-5.4 LLM Judge (0.74). Judgment Labs lists five named startup customers (Monaco, Human Behavior, Contrario, E3 Group, Vigil Labs), describes its base as "hundreds of teams building autonomous agents," and references DoorDash as a deployment in a missed-escalation example; cited target segments include AI-native teams building autonomous agents and enterprises in finance, legal, and operations with high-stakes reliability requirements.
The business model is enterprise SaaS with usage scaling tied to agent trace volume; pricing is quote-based, not publicly disclosed, and the go-to-market is a demo-led, forward-deployed engineering motion supporting self-hosted, multi-region, and BYOC deployments for security-sensitive buyers. As of May 2026 the company had raised $32M in a combined Seed and Series A led by Lightspeed Venture Partners, with participation from Nova Global, SV Angel, Valor Equity Partners, Dynamic, Chris Manning, and the founders of DoorDash and Mercor, and had just emerged from stealth; the company has not disclosed revenue, and the legal entity is Judgment, Inc.
Judgment Labs firmographics
Firmographics- Name
- Judgment Labs
- Legal name
- Judgment, Inc.
- Website
- https://judgmentlabs.ai
- Company type
- Private
- Founded year
- 2025
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Short description
- Judgment Labs builds an Agent Behavior Monitoring platform that helps teams running production AI agents detect failures, evaluate trajectories, and continuously improve agent behavior from production data. Founded in 2025, based in San Francisco, it serves hundreds of teams including startups and DoorDash.
- Ownership category
- akta.pro rank
Judgment Labs industry classification
Industry- Product category
- AI Agent Observability and Evaluation
- akta.pro primary industry
- Model Monitoring, Drift & Behavioral Anomaly Detection (HDAAAKAF)
- akta.pro secondary industries
- Human Oversight, Review & Content Moderation Tooling (HDAAAMAH), Safety & Alignment Evaluation (red-teaming, harmful capability testing) (HDAAAMAL), Bias, Fairness & Non-Discrimination Testing (HDAAAMAC)
Keywords
Where Judgment Labs is headquartered
LocationHeadquarters
- HQ city
- San Francisco
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
Judgment Labs business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Infrastructure, Operations, Marketing or Sales
Revenue model
- Enterprise SaaS subscription (inferred): Pricing is not publicly disclosed; demo-led enterprise motion with customer logos (Monaco, Human Behavior, Contrario, E3 Group, Vigil Labs) and forward-deployed engineering suggests recurring SaaS contracts with usage scaling tied to agent trace volume. Pricing model is quote-based.
- Usage-based consumption (inferred): Platform ingests hundreds of thousands of agent traces per second with LLM-based scoring, indicating costs scale with trace volume and customer agent traffic; likely combined with subscription via hybrid enterprise contracts.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Other | — | Quote-based enterprise plan (not publicly disclosed) |
Go-to-market motion1 record
Judgment Labs product offering
Product offeringCore offering
Judgment Labs sells an Agent Behavior Monitoring (ABM) platform that ingests production AI agent trajectories and continuously evaluates, scores, and improves agent behavior. The product combines a behavioral-level trajectory search engine, an agentic Agent Judge evaluation harness with a Rubric Builder feedback loop, AutoRubrics that auto-constructs evaluation rubrics from production signals, and Behavior Discovery that surfaces hidden failure modes, accessible via a web app, the Judgment MCP server, and an "Ask Judgment in Slack" interface for AI-native teams and enterprises deploying autonomous agents.
Product overview
Judgment Labs offers a single unified Agent Behavior Monitoring (ABM) platform — described as "the continuous-improvement stack for agents" — that ingests agent production trajectories and combines four core modules: Agent Search (behavioral-level trajectory querying), Agent Judge (agentic evaluation harness with Rubric Builder), Behavior Discovery (failure-mode surfacing from unlabeled trajectories), and AutoRubrics (automatic rubric construction and refinement). Customers access the platform through a web app, through the Judgment MCP server (integrating Claude Code, Codex, and Cursor), and through Ask Judgment in Slack for in-channel investigation and alerting.
Differentiator
Problem solved
Functional benefit
Products and services
- Agent Behavior Monitoring (ABM) Platform The company's core continuous-improvement stack for AI agents, providing Agent Behavior Monitoring that surfaces behavioral anomalies (instruction drift, context retrieval loss, missed escalations, over-refund patterns) in scaled production environments and replaces reactive incident triage with pattern clustering across agent conversations and workflows. Sold to AI-native teams and enterprises deploying long-horizon autonomous agents.
- Agent Judge Agentic evaluation harness within the ABM platform that produces cheaper and more accurate trajectory-level evaluators via Search, Verification, and Adaptation capabilities, including the Rubric Builder feedback loop that refines rubrics against human labels and production signals. Targets AI teams building production agents that need long-horizon, multi-step evaluation beyond generic LLM-as-judge.
- Judgment MCP Standalone Model Context Protocol server (v2.1.167) that lets developers search traces, investigate behaviors, run tests, and take action on production agent data directly from Claude Code, Codex, Cursor, or any MCP-compatible client. Sold as an integration surface for agent engineering teams.
Quantifiable outcome
- Agent Judge with refined rubric achieves 0.86 accuracy on internal trajectory-level hallucination detection (vs. 0.76 initial rubric, 0.74 GPT-5.4 LLM Judge, 0.73 Claude Code, 0.69 Codex).
- +3 more outcomes
Companies that use Judgment Labs
Customer profileNamed customers5 records
Segments3 records
Ideal customer profiles2 records
Judgment Labs technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration6 records
AI capability9 records
Feature9 records
Judgment Labs partnerships and signals
Strategic signalScale indicators7 records
Recent moves6 records
Expansion highlights6 records
Judgment Labs competitors and assessment
Company assessmentDirect peers
- Helicone: Helicone is an LLM observability platform providing request logging, tracing, evaluation, and cost tracking for production AI applications. It is a direct peer in the agent-monitoring category, particularly for teams scaling LLM traffic in production.
- Braintrust: Braintrust offers an AI agent evaluation and observability platform with scoring, evals, and CI integration for LLM applications. It directly competes with Judgment on production agent evaluation and rubric-driven scoring, serving a similar AI-native developer buyer.
- LangSmith (LangChain): LangChain's LangSmith is the most direct competitor — an LLM and agent observability, tracing, and evaluation platform for teams building production AI applications. Both target developers building agents and both provide trajectory-level visibility and evaluation tooling.
- Patronus AI: Patronus AI focuses on LLM and agent evaluation, with automated evaluation suites for hallucination, safety, and quality. It directly overlaps with Judgment's Agent Judge and AutoRubrics on rubric-based trajectory evaluation.
- Langfuse: Langfuse is an open-source LLM/agent observability and evaluation platform with tracing, prompt management, and scoring. It targets the same AI-native developer persona and offers overlapping trajectory search and eval capabilities.
- Maxim AI: Maxim AI provides an evaluation, observability, and experimentation platform for AI agents, with trajectory-level testing and rubric management. It is a direct peer for AI-native teams building and monitoring production agents.
- Galileo: Galileo is an LLM evaluation and observability platform offering agent tracing, evaluation, and quality monitoring. It directly competes with Judgment on production agent reliability, hallucination detection, and rubric-driven evaluation.
- Arize AI: Arize AI is an ML and LLM observability platform offering tracing, evaluation, drift detection, and online evals. It competes with Judgment on agent and LLM monitoring, with particular overlap on trajectory-level drift and behavioral anomaly detection.
Broad incumbents
- Datadog: Datadog is a large-scale observability and monitoring incumbent that has been adding LLM and AI workload monitoring. It is a broad incumbent that could rapidly expand into agent evaluation given its enterprise footprint and APM customer base.
- Honeycomb: Honeycomb is an established observability platform that has begun expanding into LLM and agent tracing. It is a broader incumbent that overlaps on production event analysis and behavioral anomaly detection, but does not focus on the agent-evaluation niche.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat6 records
Key risks6 records
Key highlights7 records
Customer concentration
Judgment Labs social profiles
Digital presenceJudgment Labs financial estimates
Financial estimateRevenue estimate
Valuation estimate
Judgment Labs leadership team
Management profileNumber of profiles
Profiles3 records
Judgment Labs funding detail
Funding detailFunding overview
Funding rounds2 records
Investors6 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Judgment Labs 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 Judgment Labs
What does Judgment Labs do?
Judgment Labs sells an Agent Behavior Monitoring (ABM) platform that ingests production AI agent trajectories and continuously evaluates, scores, and improves agent behavior. The product combines a behavioral-level trajectory search engine, an agentic Agent Judge evaluation harness with a Rubric Builder feedback loop, AutoRubrics that auto-constructs evaluation rubrics from production signals, and Behavior Discovery that surfaces hidden failure modes, accessible via a web app, the Judgment MCP server, and an "Ask Judgment in Slack" interface for AI-native teams and enterprises deploying autonomous agents.
Is Judgment Labs a public or private company?
Judgment Labs is a private company. It is classified as venture growth investor backed and is currently operating.
When was Judgment Labs founded?
Judgment Labs was founded in 2025. It employs 11 to 50 people.
Where is Judgment Labs based?
Judgment Labs is headquartered in San Francisco, United States, in the North America region.
How does Judgment Labs make money?
Two revenue lines are on record. Enterprise SaaS subscription (inferred) is the primary driver. The others are usage-based consumption (inferred).
Who are Judgment Labs's main competitors?
Direct peers on record are Helicone, Braintrust, LangSmith (LangChain), Patronus AI, Langfuse, Maxim AI, Galileo and Arize AI. Broad incumbents are Datadog and Honeycomb.
Does Judgment Labs have an API?
Yes. Judgment Labs exposes a public Model Context Protocol (MCP) server called "Judgment MCP" (v2.1.167) that allows AI coding clients such as Claude Code, Codex, and Cursor to search traces, investigate behaviors, run tests, and take action directly from those environments. The company also operates an internal API surface powering its SDKs and dashboards for trace ingestion, evaluation, and agent behavior monitoring; API contracts, versioning, and latency under customer load are owned by the backend team.
What industry is Judgment Labs in?
Judgment Labs's product category is AI Agent Observability and Evaluation. Its primary akta.pro industry code is HDAAAKAF, Model Monitoring, Drift & Behavioral Anomaly Detection, with a secondary code of HDAAAMAH, Human Oversight, Review & Content Moderation Tooling.