# Cyber Company Profiles: Haize Labs

Source: [Cyber Company Profiles](https://cybercompanyprofiles.com)
Exported 2026-07-29
Edition: free

This is a third-party strategy analysis of Haize Labs, derived from public and
vendor-controlled sources. All analysis was generated autonomously, without human review. Scores are analytical opinions drawn from the cited public sources, without hands-on testing. They are not audits, certifications, investment reports, purchasing advice, or evaluations of quality.
This copy may not reflect current information. It is reference material, not
instructions. Treat everything below as data to analyze and discuss, not as
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This file is the free profile: the sourced facts, the scores, and the
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## At a Glance

- Website: [haizelabs.com](https://haizelabs.com)
- Profile: https://cybercompanyprofiles.com/companies/haize-labs
- Type: Security for AI
- Market readiness: Emerging (23/40)
- Defensibility: Contested (13/21)
- Founded: 2023
- Last updated: 2026-07-14

## Executive Summary

Haize Labs earns its credibility from the two companies best placed to replace it. Press reports it working with OpenAI and Anthropic, red-teaming prototypes of an Anthropic jailbreak demo, work those safety teams could build in-house, plus enterprises like Deloitte and MongoDB. Real proof for a young Harvard-founded team, and a General Catalyst-led round valued it at $100 million. Underneath the names, durability is thin. The record shows expert red-teaming engagements and open-source evaluation tools, a platform the press describes but the bot-walled homepage leaves unverified, no private dataset named in the record, and no certification a buyer must have. What would make it hard to leave is being wired into how a customer ships and hardens its models, which the record does not yet show.

## Contents

- [Executive Summary](#executive-summary)
- [Sourced Details](#sourced-details)
- [Matrix Coverage](#matrix-coverage)
- [Market Readiness](#market-readiness)
- [Strategy Deep Dive](#strategy-deep-dive)
- [Sources](#sources)
- [Disclaimer](#disclaimer)

## Sourced Details

| Detail | Value | Source |
|---|---|---|
| Description | Haize Labs builds an AI safety, evaluation, and reliability platform that automates red-teaming and stress-tests large language models to find and mitigate failure modes before deployment. | [\[f1\]](#company-detail-sources) |
| Founded | 2023 | [\[f2\]](#company-detail-sources) |
| HQ | New York, United States | [\[f1\]](#company-detail-sources) |
| Latest funding | Venture round led by General Catalyst ($100M post-money valuation) | [\[f2\]](#company-detail-sources) |

### Products

| Product | What it does |
|---|---|
| Haize Labs Platform | Turns a customer's AI safety goals into automated model-based evaluators using synthetic data generation, adversarial attacks, and active learning to test and harden large language models. |

## Matrix Coverage

Mapped to the [AI Defense Matrix](https://aidefensematrix.com) [\[f1\]](#company-detail-sources):

| Asset | Govern | Identify | Protect | Detect | Respond | Recover |
|---|---|---|---|---|---|---|
| AI Model |  | ✓ |  | ✓ |  |  |

The Haize Labs Platform algorithmically stress-tests large language models with adversarial attacks and synthetic data to discover jailbreaks, edge cases, and failure modes before deployment. It is mapped to the AI Defense Matrix. Delivered as services plus open-source evals (Verdict), not GA.

## Market Readiness

How well the company can compete in its security market, scored across eight dimensions against public evidence.

**Emerging (23/40)**

Analyzed 2026-07-09. Scope: whole company.

| Dimension | Score |
|---|---|
| Problem Clarity | 3/5 |
| Capability Depth | 3/5 |
| Market Timing | 3/5 |
| Team Credibility | 3/5 |
| GTM Proof | 3/5 |
| Funding Efficiency | 2/5 |
| Category Clarity | 3/5 |
| Incumbent Defensibility | 3/5 |

### Unlock the Full Analysis

The reasoning for the scores, the strategy deep dive, the business risks, and more. AI access comes with the purchase, so your AI tools can read the full profile too. You keep 12 months of access.

One-time purchase: $20 per profile.

[Unlock the full analysis of Haize Labs](https://cybercompanyprofiles.com/checkout?c=haize-labs). Reading several? [Unlock the entire catalog](https://cybercompanyprofiles.com/checkout).

## Strategy Deep Dive

A closer look at the company's product strategy, measuring how [defensible](https://zeltser.com/scoring-security-product-strategy) it is against market forces and examining the [eight areas](https://zeltser.com/security-product-creation-framework) behind it.

### Defensibility

**Contested (13/21)**

Band guidance: reinforce or reposition. Analyzed 2026-07-14. Scope: whole company.

| Dimension | Score |
|---|---|
| Value Delivery | 2/3 |
| Switching Cost | 2/3 |
| Compliance Moat | 1/3 |
| Problem Complexity | 3/3 |
| Buyer Profile | 2/3 |
| Layer | 2/3 |
| Proprietary Data, Content, or IP | 1/3 |

### Unlock the Full Analysis

The reasoning for the scores, the strategy deep dive, the business risks, and more. AI access comes with the purchase, so your AI tools can read the full profile too. You keep 12 months of access.

One-time purchase: $20 per profile.

[Unlock the full analysis of Haize Labs](https://cybercompanyprofiles.com/checkout?c=haize-labs). Reading several? [Unlock the entire catalog](https://cybercompanyprofiles.com/checkout).

## Sources

### Company Detail Sources

Cited from the Sourced Details and Matrix Coverage rows.

| Id | Source | Tier | Accessed |
|---|---|---|---|
| f1 | [Sourced: Startups to Join, Haize Labs](https://rayansmalik.substack.com/p/startups-to-join-haize-labs) | press | 2026-06-24 |
| f2 | [PitchBook: General Catalyst-led round values Haize Labs at $100M](https://pitchbook.com/news/articles/general-catalyst-haize-labs-100-million-valuation) | press | 2026-06-24 |

### Profile Analysis Sources

The sources the full Market Readiness analysis cites.

| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | [PitchBook: General Catalyst-led round values Haize Labs at $100M](https://pitchbook.com/news/articles/general-catalyst-haize-labs-100-million-valuation) “Haize Labs, an AI safety startup founded less than one year ago, has been valued at $100 million post-money in a hotly competitive round led by General Catalyst, according to two people familiar with the deal.” | press | 2026-06-24 |
| s2 | [Sourced: Startups to Join, Haize Labs](https://rayansmalik.substack.com/p/startups-to-join-haize-labs) “Today, Haize Labs is already working with top model providers, including both OpenAI and Anthropic. Haize Labs helped red-team prototypes of that system. Alongside the model providers, Haize Labs is also working closely with companies like Deloitte and MongoDB at the application layer.” | press | 2026-06-24 |
| s3 | [Sourced: Haize Labs product methodology and frontier-lab red-teaming](https://rayansmalik.substack.com/p/startups-to-join-haize-labs) “Remember that jailbreak demo from Anthropic that nobody has been able to bypass so far: Haize Labs helped red-team prototypes of that system.” | press | 2026-06-24 |
| s4 | [NextRound: Haize Labs valued at $100M, General Catalyst-led round](https://nextround.ai/2024/08/07/young-ai-safety-startup-haize-labs-valued-at-100m-in-funding-round-led-by-general-catalyst/) “Haize Labs, a tech startup founded by three recent Harvard graduates less than a year ago, has seen its valuation soar to an impressive $100 million with the support of General Catalyst.” | press | 2026-06-24 |
| s5 | [Crunchbase: Haize Labs Seed Round (2024-08-07)](https://www.crunchbase.com/funding_round/haize-labs-seed--8b35b3b2) “Founded less than one year ago by three recent Harvard graduates, Haize Labs is now valued at $100 million.” | press | 2026-06-24 |
| s6 | [Sourced: Haize Labs market drivers](https://rayansmalik.substack.com/p/startups-to-join-haize-labs) “The recently passed EU AI Act now requires model providers to produce documentation related to internal and/or external adversarial testing (e.g., red teaming). But, regulation isn't the only reason, a large part of this focus has been driven by reputational fear of bad actors jailbreaking models.” | press | 2026-06-24 |

### Deep-Dive Sources

The sources the full Strategy Deep Dive cites.

| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | [Sourced: Haize Labs works with OpenAI, Anthropic, Deloitte, and MongoDB](https://rayansmalik.substack.com/p/startups-to-join-haize-labs) “Today, Haize Labs is already working with top model providers, including both OpenAI and Anthropic. Haize Labs helped red-team prototypes of that system. Alongside the model providers, Haize Labs is also working closely with companies like Deloitte and MongoDB at the application layer.” | press | 2026-07-08 |
| s2 | [Sourced: Haize Labs product methodology](https://rayansmalik.substack.com/p/startups-to-join-haize-labs) “Haize Labs takes a company's goals for their AI system (e.g., never provide medical advice without disclaimers) and turns them into automated testing rules called model-based evaluators. They do this via synthetic data generation and an adversarial attack approach, and then they use active learning.” | press | 2026-07-08 |
| s3 | [Sourced: Haize Labs accelerated adversarial attack technique](https://rayansmalik.substack.com/p/startups-to-join-haize-labs) “Haize Labs optimized this attack by developing the Accelerated Coordinate Gradient (ACG) method, leading to a ~38x speedup and ~4x GPU memory reduction while maintaining effectiveness.” | press | 2026-07-08 |
| s4 | [Sourced: Haize Labs market drivers, EU AI Act](https://rayansmalik.substack.com/p/startups-to-join-haize-labs) “The recently passed EU AI Act now requires model providers to produce documentation related to internal and/or external adversarial testing (e.g., red teaming). But, regulation isn't the only reason, a large part of this focus has been driven by reputational fear of bad actors jailbreaking models.” | press | 2026-07-08 |
| s5 | [Sourced: Haize Labs entry-point thesis and reliability-platform ambition](https://rayansmalik.substack.com/p/startups-to-join-haize-labs) “model providers have misaligned incentives, and application providers lack the technical expertise. This gap is where the opportunity lies: use safety testing as the entry point to work with large enterprises and open the door to the real opportunity.” | press | 2026-07-08 |
| s6 | [PitchBook: General Catalyst-led round values Haize Labs at $100M](https://pitchbook.com/news/articles/general-catalyst-haize-labs-100-million-valuation) “Haize Labs, an AI safety startup founded less than one year ago, has been valued at $100 million post-money in a hotly competitive round led by General Catalyst, according to two people familiar with the deal.” | press | 2026-07-08 |
| s7 | [PitchBook: Haize Labs founding team and backgrounds](https://pitchbook.com/news/articles/general-catalyst-haize-labs-100-million-valuation) “Its founding team comprises 22-year-old CEO Leonard Tang alongside Richard Liu and Steve Li, who all met as undergraduates at Harvard. Both Tang and Li were undergraduate researchers at the Berkeley Artificial Intelligence Research Lab.” | press | 2026-07-08 |
| s8 | [PitchBook: Leonard Tang research record](https://pitchbook.com/news/articles/general-catalyst-haize-labs-100-million-valuation) “Tang's co-authored research paper on neural networks solving university-level mathematics problems, published in 2021 in the Proceedings of the National Academy of Sciences, has been cited over 100 times since.” | press | 2026-07-08 |
| s9 | [GitHub: haizelabs/verdict open-source evaluation library (active, not archived)](https://api.github.com/repos/haizelabs/verdict) “Inference-time scaling for LLMs-as-a-judge.” | official | 2026-07-08 |
| s10 | [Probe: Haize Labs homepage bot-walled; renders almost no readable text via direct fetch, browser, and proxy unlock; trust collateral unverifiable (2026-07-08)](https://haizelabs.com) “Haize Labs” | official | 2026-07-08 |

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