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Hael vs Holistic AI

Based on public documentation as of July 2026. holisticai.com · Updated 6 July 2026 · 8 min read
Verdict
Holistic AI is one of the most visible names in AI assurance, with roots in algorithm auditing and bias assessment: Holistic AI publicly positions itself as "The Enterprise AI Governance Platform … trusted by global enterprises running AI at scale" organised around Identify, Protect and Enforce, with dedicated product surfaces for Bias Audit, LLM Testing and AI Red Teaming and a dedicated NYC Bias Audit solution for Local Law 144 (https://www.holisticai.com/, https://www.holisticai.com/ai-governance-platform, https://www.holisticai.com/nyc-bias-audit). The honest split: organisations wanting third-party audit and assurance work, including bias-audit obligations such as NYC Local Law 144, should have Holistic AI on the list; organisations wanting the operating record that generates and maintains their own governance artefacts, and vendors needing reviews answered from it, are evaluating a different category, which is Hael's. Where an organisation needs both, the two are complementary rather than exclusive, and the table reflects that honestly. GRC and governance tools tell you which documents you are missing; Hael creates them and runs the controls behind them.
Hael is for
Teams that must produce the AI-specific artefacts a regulator or enterprise buyer reads, govern agents at runtime, and answer AI diligence from a single system record.
Holistic AI is for
Enterprises that need third-party audit, bias assessment, LLM testing and AI red-teaming — particularly for hiring tools under NYC Local Law 144 and similar bias-audit obligations — delivered as an assurance service alongside a governance platform.
Comparison

Side by side.

AxisHaelHolistic AI
Framework coverage breadthEU AI Act, ISO/IEC 42001, NIST AI RMF, GDPR Article 22, DORA, SOC 2, Colorado ADMT Act, Texas TRAIGA, NYC LL144, California ADMT, Illinois HB 3773, Utah AI Policy Act, Korea AI Basic Act, UK AI framing — plain-English guides, per-framework readiness tools and cited briefs.Publicly headlines end-to-end coverage of regulatory compliance across enterprise AI, with dedicated depth on NYC Local Law 144 (AEDT bias audit); a single itemised public inventory of every framework covered is not published on the platform page.
Document generation vs trackingGenerates the substantive artefact itself — Annex IV technical files, model cards, impact assessments, questionnaire answers, trust-centre pages — from the same live registry that runs the controls.Publicly positioned to "Discover, assess, and govern every AI system across your enterprise" with continuous monitoring and reporting, "audit-ready from day one"; substantive generation of the underlying regulatory artefact (Annex IV technical file, system-level model card) is not called out as a distinct product surface on the platform page.
Agent-native governanceAgent registry, per-agent lifecycle state, prompt and tool-use policy, human-in-the-loop gates and tamper-evident audit chain — built for systems that act, not only advise.Publicly covers "every AI system across your enterprise, from shadow AI to agentic workflows" under the Identify surface; itemised runtime controls for agents (per-agent scopes, tool-use policy, HITL gates, tamper-evident audit chain) are not detailed on the public platform page.
Questionnaire answeringAnswers inbound enterprise AI questionnaires from the governance record itself — evidence-cited answers, one canonical answer library, coordinator workflow, held-open gaps with dates.An inbound questionnaire-answering surface for the vendor's own team is not publicly documented as a distinct product line on the platform page.
Trust centrePublic trust centre generated from the same governance record — model summaries, framework posture, sub-processors, incidents and change notice.A public customer-facing trust-centre product for the vendor's own reviewers is not publicly documented on the platform page.
Target buyerAI-native vendors and regulated enterprises where the same team must produce the evidence, answer the questionnaire and run the controls.Publicly cites global enterprise customers including Unilever, Mapfre, Johnson Controls, PMI, eBay, GE Healthcare, SLB and Allegis on the platform and homepage.
Pricing transparencyPublic pricing page with tier structure; enterprise terms available on request.Not publicly documented. Pricing is quoted via sales; no public price page is published as of the dateline.
Third-party audit and assurance servicesNot offered; Hael is the record auditors and assurers work against, and partners deliver assurance on it.Publicly offers a dedicated NYC Bias Audit solution for Local Law 144 with named case studies (for example, Hired), and publishes bias-audit whitepapers and papers on the AEDT law — a distinct assurance-service line alongside the platform.

Where Holistic AI is genuinely credible

Holistic AI is one of the most visible assurance names in the market and, for the shape of buyer it is built for, a serious shortlist entry. Its platform is publicly organised around Identify (AI Discovery, Inventory, Monitoring), Protect (Risk Management, LLM Testing, Bias Audit, AI Red Teaming) and Enforce (Policies & Controls, Compliance, Workflows, Reporting) — an unusually broad assurance-first product surface (https://www.holisticai.com/ai-governance-platform). It publishes a dedicated NYC Bias Audit solution for Local Law 144, with case studies including Hired, and publishes multiple public papers on the AEDT bias-audit regime (https://www.holisticai.com/nyc-bias-audit, https://www.holisticai.com/case-study/hired, https://www.holisticai.com/papers/whitepaper-nyc-bias-audit). Global enterprise customers referenced publicly include Unilever, Mapfre, Johnson Controls, PMI, eBay, GE Healthcare, SLB and Allegis (https://www.holisticai.com/ai-governance-platform). For organisations whose immediate need is third-party assurance — a bias audit, an LLM evaluation, an AI red-team engagement, or LL144 compliance — Holistic AI is a credible provider.

What to evaluate in any AI governance platform

Three questions separate this category more than any feature list. Does the platform generate the governance artefacts themselves, the technical files, assessments, model cards and questionnaire answers regulators and buyers actually read, or does it track that they exist somewhere else? Are AI agents governed as first-class systems, with declared scopes and runtime controls, or recorded as inventory entries? And does it serve the vendor lane, answering inbound security and AI questionnaires from the governance record, or only the internal oversight lane? Score any platform, including Hael, against those three and the shortlist writes itself.

How Hael differs

Hael's premise is that the document is the obligation: every artefact is generated from each system's live operating record, agents are governed as systems with scopes and runtime controls, and the same record answers enterprise questionnaires with citations, runs a trust page, and shows readiness per framework. It is built by regulatory practitioners for the organisations that will be assessed on the artefacts, and for the vendors whose deals are gated on them.

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Applicability
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What's expected
Risk classification · governance · documentation · oversight
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Effort
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INDICATIVE · NOT LEGAL ADVICE
This comparison is drawn from each vendor's public documentation on the dateline shown. Where a fact is not publicly documented, we say so rather than guess. Corrections welcome.
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