What Haize Labs does

Haize Labs is a New York-based, privately held AI safety and reliability company founded in 2023 that builds expert-level AI agents for mission-critical enterprise workflows. Its flagship product is the proprietary Reliability Harness, a technology suite that combines agent architecting, AI supervisor monitoring, exhaustive simulation testing (847+ scenarios at a cited 98.7% pass rate), adversarial red-teaming, runtime guardrails, and human-in-the-loop annotation tooling to deploy agents that the company reports run at 99.9% uptime and 42ms latency. The platform is applied to verticals where reliability is regulated or reputationally consequential: insurance claims adjudication, healthcare, compliance, finance, risk operations, and security.

Haize Labs generates revenue through a custom enterprise engagement model, structured as a five-phase process (Exploratory Phase, Agent Development, Customer Validation, Knowledge Transfer, Ongoing Improvement) sold via direct field sales and a consultative 'Talk to an Expert' motion. Publicly named customers include OpenAI, Anthropic, Air Canada, Epic Games, Deloitte, GovTech, and Gránit Bank, and the company has closed a seed funding round in August 2024 led by General Catalyst. Beyond the core agent platform, Haize Labs maintains an active research arm that has open-sourced nine named artifacts on GitHub and arXiv, including the Verdict LLM-as-a-judge library, TournO reward-modeling method, Constitutional Classifiers, Cascade multi-turn red-teaming, Bijection Learning jailbreaks, ACG adversarial optimization, j1-micro/j1-nano reward models, Safe RBAC RAG with MongoDB, and a Red-Teaming Resistance Leaderboard hosted on Hugging Face. The company is SOC 2 Type II certified and operates a small team (approximately 15 named personnel including co-founders Leonard Tang and Steve Li) under legal entity Haize Labs, Inc.

Name

Haize Labs

Legal name

Haize Labs, Inc.

Website

https://haizelabs.com

Company type

Private

Founded year

2023

Operating status

Operating

Headcount range

11–50 employees

Short description

Haize Labs builds a proprietary Reliability Harness that designs, tests, red-teams, and monitors expert-level AI agents for mission-critical enterprise workflows in insurance, healthcare, compliance, finance, risk, and security, serving customers like OpenAI, Anthropic, Deloitte, Air Canada, and Gránit Bank.

Ownership category

akta.pro rank

Product category

AI Safety and Reliability Software

NAICS

Computer Systems Design and Related Services (54151), Other Computer Related Services (541519)

SIC

Services-Prepackaged Software (7372), Services-Computer Programming Services (7371)

akta.pro primary industry

Responsible AI, Security & Privacy Platforms (Safety, Guardrails, PII) (HDAEANAG)

akta.pro secondary industries

AI Application Enablement Platforms (Copilot/Agent Frameworks, SDKs) (HDAEANAJ), AI Observability, Monitoring & Evaluation Platforms (Drift, Quality, Safety) (HDAEANAF), Agents & Autonomous Workflows (Tool Use, Planning, Multi-Agent) (HDAAACAF), End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management) (HDAEANAA)

Keywords

• AI agent reliability
• AI safety testing
• LLM red-teaming
• AI compliance automation
• Mission-critical AI agents

Headquarters

HQ city

New York

HQ country

United States

HQ region

North America

Offices1 record

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Marketing or Sales, Operations

Revenue model

1. AI Agent Development & Deployment Services: Haize Labs engages enterprise clients through a structured 5-step process (Exploratory Phase, Agent Development, Customer Validation, Knowledge Transfer, Ongoing Improvement) to build custom expert-level AI agents. Revenue appears to come from professional services and agent development engagements.

Pricing tiers

Go-to-market motion1 record

Distribution channels1 record

Marketing channels7 records

Core offering

Haize Labs builds and deploys expert-level AI agents for mission-critical enterprise workflows through its proprietary Reliability Harness technology suite. The platform combines agent architecting, AI supervisor models, simulation testing, adversarial red-teaming, runtime guardrails, and human-in-the-loop annotation tooling to deliver production-grade AI agents with 99.9% uptime and 42ms latency for verticals including insurance, healthcare, compliance, finance, risk operations, and security.

Product overview

Haize Labs is a B2B AI trust, safety, and reliability company that offers a unified product portfolio centered on its proprietary Reliability Harness — a technology suite for building and deploying expert-level AI agents in mission-critical settings. The platform is modular, comprising the core Reliability Harness engine, the Verdict open-source library for LLM-as-a-judge evaluation, the Safety Detector API for input safety scanning, and multiple research-driven tools (TournO, Cascade, Constitutional Classifiers, ACG, DSPy Red-Teaming, Safe RBAC RAG, j1-micro/nano reward models, and the Red-Teaming Resistance Leaderboard) that collectively cover the full lifecycle of agent development, testing, deployment, and continuous improvement. The flagship AI Agents product is deployed for use cases in insurance, healthcare, compliance, financial risk operations, and security.

Differentiator

Problem solved

Functional benefit

Products and services

• Haize Reliability Harness Proprietary, end-to-end technology suite for building and operating AI agents in production. Comprises Agent Architecting (workflow design and post-training), Supervisor AI models that monitor other agents, Simulation Testing across 847+ scenarios, Red-Teaming, runtime Guardrails, and Annotation Tooling. Sold as part of Haize Labs' enterprise engagement design for mission-critical workloads.
• Mission-Critical AI Agents Expert-level AI agents deployed for mission-critical operations including debt collection (DebtCollectionVoice), claims processing and adjudication, healthcare, compliance, financial risk operations, and security. Built on the Reliability Harness with agent specifications, supervisor oversight, simulation validation, and continuous improvement cycles. Deployed for enterprise customers via a 5-step engagement design process.
• Verdict Library Open-source Python library for scaling LLM-as-a-judge evaluation. Provides ensemble judges (max-voting), rubric fan-out (evaluating each rubric criterion independently), batch evaluation, counterfactual experimentation, extractor methods, parallel batch evaluation, and automatic retries/rate-limiting. Used by developers building robust automated AI evaluation pipelines.
• Safety Detector API Public API endpoint that scans inputs and retrieved documents for jailbreaks and prompt injections. Integrated into the Safe RBAC RAG solution to defend against malicious instructions embedded in retrieved RAG documents. Sold to enterprise customers deploying secure RAG applications.
• TournO (Tournament Optimization) Open-source reward-modeling method for reinforcement learning in non-verifiable domains. Directly incorporates pairwise tournament-style comparisons into the RL reward signal, yielding better local calibration than standard pointwise reward models. Validated on HealthBench with significant outperformance over GRPO baselines. Released as open-source code and an arXiv paper.
• Cascade (Automated Multi-Turn Red-Teaming) Automated multi-turn red-teaming attack system using beam search over parallel conversation branches to discover jailbreak trajectories. State-of-the-art attack achieving higher attack success rates than expert human red-teaming on frontier models. Released as a research tool with an accompanying blog post.
• Constitutional Classifiers Constitutional AI-based defense mechanisms designed to defend against universal jailbreaks across thousands of hours of red teaming. Developed in partnership with AI21 Labs for Jamba LLM alignment, with a research paper on arXiv (2501.18837).
• j1-micro and j1-nano Open-source reward models at 1.7B (j1-micro) and 600M (j1-nano) parameters, designed to deliver competitive performance in extremely compact form for use as pointwise and pairwise judges in RLHF and TournO reward shaping.
• ACG (Accelerated Coordinate Gradient) Optimized adversarial attack algorithm yielding approximately 38x speedup over the GCG (Greedy Coordinate Gradient) algorithm and 4x GPU memory reduction, enabling practical large-scale adversarial testing of LLMs without sacrificing attack success rate. Open-source research release.
• DSPy Red-Teaming Open-source red-teaming framework using DSPy's MIPRO optimizer to compile a multi-layer Attack-Refine language program into an effective adversarial prompt generator, achieving 44% attack success rate against Vicuna-7B-v1.5 without specific prompt engineering.
• Red-Teaming Resistance Leaderboard Public benchmark released in collaboration with Hugging Face evaluating LLM robustness against high-quality human adversarial prompts from AdvBench, RedEval, SAP, and other datasets. Categorizes vulnerabilities into Harm & Violence, Criminal Conduct, Unsolicited Counsel, and NSFW.
• Safe RBAC RAG Open-source RAG solution implementing document-level role-based access controls (RBAC) with MongoDB Atlas, integrated with the Haize Labs Safety Detector API to defend against jailbreaks and prompt injections in retrieved documents. Targeted at enterprise RAG deployments requiring fine-grained access control propagation.

Quantifiable outcome

• 99.9% production uptime for deployed AI agents
• +8 more outcomes

Named customers9 records

Segments2 records

Ideal customer profiles2 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

Integration4 records

AI capability12 records

Feature13 records

Partnerships

Three partnerships are on record, tiered core and minor.

• AI21 LabscoreStrategic or Co-development Partner · 9 December 2024Haize Labs partnered with AI21 Labs to align the Jamba large language model with ethical and operational business needs. Haize Labs provided automated adversarial testing (dozens of thousands of adversarial prompts), AI and human feedback loops, and transparent frameworks. The collaboration developed a Business AI Code of Conduct with 60 tenets mapped to OECD AI Principles, achieving improved alignment scores and customizable system instructions for Jamba.
• GoodfireminorStrategic or Co-development PartnerHaize Labs collaborated with Goodfire to leverage the Goodfire platform for mechanistic interpretability-based red-teaming. Using Goodfire's Sparse Autoencoder (SAE) features and activation steering capabilities, Haize Labs demonstrated red-teaming methods that manipulate model internals to provoke harmful behaviors, as an alternative to traditional prompt-based testing.
• Hugging FaceminorStrategic or Co-development PartnerHaize Labs released the Red-Teaming Resistance Leaderboard in collaboration with Hugging Face. The leaderboard benchmarks LLM robustness against high-quality human adversarial attacks across multiple categories including Harm and Violence, Criminal Conduct, Unsolicited Counsel, and NSFW.

Scale indicators4 records

Recent moves6 records

Expansion highlights6 records

Direct peers

• Patronus AI: Enterprise LLM evaluation and safety platform focused on detecting hallucinations, PII, and brand risk. Most directly comparable to Haize Labs in product scope (LLM-as-a-judge, red-teaming, enterprise reliability) and target buyer.
• Lakera AI: AI security platform offering red-teaming, prompt-injection defense, and guardrails for LLM applications — overlapping closely with Haize's Safety Detector API, red-teaming, and runtime guardrails offerings.
• Calypso AI: AI security and observability platform for enterprise generative AI, with red-teaming, policy enforcement, and audit trails — highly comparable to Haize's mission-critical reliability positioning.
• Arize AI: AI observability and LLM evaluation platform providing drift detection, tracing, and online evaluations — overlapping with Haize's simulation testing and Supervisor-style monitoring components.
• WhyLabs: AI observability platform offering LLM and ML monitoring, guardrails, and quality evaluation — directly comparable to Haize's evaluation, guardrails, and anomaly detection capabilities.
• Galileo: Enterprise LLM evaluation and observability platform with guardrails and hallucination detection — comparable to Haize's Reliability Harness components for production LLM agents.
• Fiddler AI: AI observability and explainability platform for ML and LLM applications — overlapping with Haize's monitoring, evaluation, and audit/explainability tooling for regulated enterprise use cases.
• LangSmith (LangChain): LLM development platform offering tracing, evaluation, and testing tooling for LLM applications — overlapping with Haize's agent evaluation and reliability infrastructure.

Broad incumbents

• Weights & Biases: Broader MLOps platform that has expanded into LLM evaluation and tracing — adjacent to Haize's Reliability Harness but serving a wider ML/AI tooling audience rather than mission-critical AI agents specifically.

Emerging players

• Giskard: Open-source AI testing and red-teaming platform for LLMs, focused on vulnerability scanning and evaluation — comparable to Haize's open-source red-teaming and Verdict-style evaluation tooling.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks6 records

Key highlights7 records

Customer concentration

• Xx.com/haizelabs
• LinkedInlinkedin.com/company/haizelabs

Compliance1 record

Revenue estimate

Valuation estimate

Number of profiles

Profiles14 records

Funding overview

Funding rounds1 record

Investors8 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Haize Labs