AI Governance Software Vendor Visibility Index

Every Engine Names the Same Five Vendors First

Share of answers naming each core AI governance vendor, by engine. The grey line spans the three engines; the dark tick is all three combined.

ChatGPT Gemini Perplexity All engines

0%10%20%30%40%50%60%

All

1Credo AI

49.3%45.5–53.0

2IBM

44.9%41.2–48.7

3Holistic AI

31.0%27.6–34.5

4OneTrust

28.9%25.6–32.4

5ModelOp

22.9%19.9–26.2

6ServiceNow

13.1%10.8–15.9

7Trustible

7.3%5.6–9.5

8Monitaur

6.3%4.7–8.3

9Modulos

6.0%4.4–8.0

10SAS

6.0%4.4–8.0

11ValidMind

5.7%4.1–7.7

12Saidot

5.4%3.9–7.3

Source: Ranking Atlas, AI Governance Software Vendor Visibility Index, October 2026 edition. 112 buyer questions, each asked twice on ChatGPT, Gemini and Perplexity, on 18 October 2026: 224 answers per engine, 672 in all. Right column: share of all 672 answers, with its 95% interval (Wilson). Data: ai-governance-vendor-visibility-index.csv

Show the data as a table

Vendor	ChatGPT	Gemini	Perplexity	All engines	95% interval
Credo AI	112 of 224 (50.0%)	97 of 224 (43.3%)	122 of 224 (54.5%)	331 of 672 (49.3%)	45.5% to 53.0%
IBM	107 of 224 (47.8%)	86 of 224 (38.4%)	109 of 224 (48.7%)	302 of 672 (44.9%)	41.2% to 48.7%
Holistic AI	72 of 224 (32.1%)	53 of 224 (23.7%)	83 of 224 (37.1%)	208 of 672 (31.0%)	27.6% to 34.5%
OneTrust	65 of 224 (29.0%)	56 of 224 (25.0%)	73 of 224 (32.6%)	194 of 672 (28.9%)	25.6% to 32.4%
ModelOp	56 of 224 (25.0%)	43 of 224 (19.2%)	55 of 224 (24.6%)	154 of 672 (22.9%)	19.9% to 26.2%
ServiceNow	45 of 224 (20.1%)	16 of 224 (7.1%)	27 of 224 (12.1%)	88 of 672 (13.1%)	10.8% to 15.9%
Trustible	5 of 224 (2.2%)	16 of 224 (7.1%)	28 of 224 (12.5%)	49 of 672 (7.3%)	5.6% to 9.5%
Monitaur	13 of 224 (5.8%)	10 of 224 (4.5%)	19 of 224 (8.5%)	42 of 672 (6.3%)	4.7% to 8.3%
Modulos	12 of 224 (5.4%)	10 of 224 (4.5%)	18 of 224 (8.0%)	40 of 672 (6.0%)	4.4% to 8.0%
SAS	14 of 224 (6.3%)	9 of 224 (4.0%)	17 of 224 (7.6%)	40 of 672 (6.0%)	4.4% to 8.0%
ValidMind	12 of 224 (5.4%)	13 of 224 (5.8%)	13 of 224 (5.8%)	38 of 672 (5.7%)	4.1% to 7.7%
Saidot	20 of 224 (8.9%)	3 of 224 (1.3%)	13 of 224 (5.8%)	36 of 672 (5.4%)	3.9% to 7.3%

Key Findings

1. Credo AI is the most-named vendor on every engine. It was named in 49.3% of answers overall and placed first on ChatGPT (50.0%), Gemini (43.3%) and Perplexity (54.5%).
2. IBM is a close second and leads for three buyer types. IBM, counted through watsonx.governance and OpenPages model risk, was named in 44.9% of answers. It leads for bank risk and compliance officers (70.2%), heads of AI (64.3%) and public sector buyers (45.2%).
3. Model risk buyers get a different list. For model risk management leads, SAS leads (42.9%), followed by IBM (36.9%) and ValidMind (33.3%). Credo AI, first overall, was named in 10.7% of these answers.
4. Platform modules hold 37.4% of core mentions. Four of the top ten core vendors are broad platforms counted through a named AI governance module: IBM, OneTrust, ServiceNow and SAS.
5. Adjacent products take almost half the mentions. Of 3,457 counted vendor mentions, 1,690 (48.9%) were adjacent products, and 176 of the 672 answers named no core vendor, including all 96 answers to the open questions.

What the Data Shows

Credo AI and IBM hold the top two places everywhere

Between them, Credo AI and IBM lead every buyer type except model risk, and they were named together in 235 answers. The top two hold 35.8% of core mentions and the top five hold 67.3%, so a handful of names account for most of the category, with Holistic AI, OneTrust and ModelOp completing the group.

Inventory questions favour the platforms buyers already run

Twenty-one companies in the core class sell a broad platform and count here only through a named AI governance product. Their share of core mentions depends on the question. On inventory and registry questions it was 48.2%. On risk assessment questions it was 28.6% and on cost and procurement 26.1%. When buyers ask where to keep a record of every AI system, the engines lean towards platforms they may already run.

Model risk, European and healthcare buyers see a different field

Model risk leads get SAS, IBM and ValidMind at the top, with Credo AI far behind. For European buyers, Modulos and Saidot (19.0%) enter the picture. Healthcare buyers have the most answers with no core vendor, and Ferrum Health appears only in their top five. A vendor ranked mid-table overall can be a leader for one of these buyers and almost absent for the rest.

ChatGPT moved most between runs below the top five

ChatGPT had the lowest core rank correlation between its two runs and Perplexity the highest (Table 4). The engines also disagree with each other below the leaders: in the adjacent table, Arthur was named in 15.6% of Gemini answers and 1.8% of ChatGPT answers. Below the leaders, the engine a buyer happens to use shapes the list they see.

Suites and ML platforms fill almost half the answers

One answer in four named no core vendor. That includes every answer to the 16 open questions, which asked about the governance problem rather than for products. The engines named 54 core vendors, and only 12 cleared the main-table line.

How to Read the Tables

The four views answer different questions: Tables 1 and 2 rank vendors overall, the buyer-type view shows the top five for each buyer type, and the engine view shows each engine's own top five. A vendor's position often differs between views, and that difference is usually the most useful thing to know.

Why the Line Is 7 Questions

A vendor is ranked only if it was named in 7 or more of the 112 questions in at least one engine run. Below that, the difference between one appearance and two reflects run-to-run variation more than a real gap. 42 further core entries and 73 further adjacent entries were named at least once but fell below the line. All of them are in the appendix and the CSV. Two core entries came close: Yields, with a best single run of 6 questions, and Airia, with 5. If a product was never named, that is a result rather than an omission.

How We Measured

Questions. 112 questions written in the voice of real buyers: 14 for each of eight buyer types, covering shortlist, capability and open problem questions. No question names a brand. Every question was reviewed for wording that would favour one kind of vendor, and the set was fixed before collection. One question (EU03) asks specifically for European vendors, so it favours them; non-European vendors named in its answers are still counted.

Collection. Each question was asked twice on ChatGPT, Gemini and Perplexity on 18 October 2026 (Singapore time), with no system message or prior conversation, set to US location and English. All 672 answers were collected.

Counting. A company counts once per answer, however many times it is named. A mention counts when the answer recommends or lists the product as an option. Products named only as something to avoid, as the buyer's existing tools or environment, as an integration target or as a source do not count.

Classes. Core and adjacent are defined under Tables 1 and 2. Tools that only block, redact or test AI at runtime count as adjacent here. Each product is judged against this index's definition alone, whatever its class in other Ranking Atlas indexes. Legal and contract tools, AI model providers and health record systems are out of scope.

Score. Visibility % is the mean of the six engine-run percentages, so each engine counts equally.

Acquired products. A product bought or renamed by another company counts under its owner on the collection date, and the label says so wherever the earlier brand was named, for example Veeam (incl. Securiti) and Optro (incl. AuditBoard). Where a single answer named both brands, it counts once.

How Consistent Each Engine Was Between Runs

Engine	Core: rank correlation	Core: top-10 overlap	Adjacent: rank correlation	Adjacent: top-10 overlap
ChatGPT	0.634	9 of 10	0.579	10 of 10
Gemini	0.741	9 of 10	0.645	9 of 10
Perplexity	0.927	10 of 10	0.874	9 of 10

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All three engines returned the same leaders twice, and Perplexity was the most stable. ChatGPT and Gemini varied more among rarely named vendors, which is why the index averages two runs per engine and does not rely on one.

Limitations

This is one collection window, so answers can change week to week. Real users with their own history, location or settings may see different answers. Coding was done by a single coder against a fixed codebook, with every judgement call logged. Where an answer names a platform company without its governance product, it counts as adjacent, which can understate that company's core score. Counts measure how often a vendor is named, not whether the recommendation is favourable. Results for a buyer type rest on 14 questions. Vendors mentioned only once in running text may be missing, so the count of rarely named vendors is a minimum.

The 112 buyer questions, grouped by buyer type

Bank chief risk or compliance officer (financial services, 5,000+ staff)

ID	Stage	Question
CR01	Shortlist	We are a bank with 20,000 staff and hundreds of AI models in use. Which AI governance platforms should be on our shortlist? Compare the leading vendors.
CR02	Shortlist	Which AI governance software is strongest for a heavily regulated financial institution, and why?
CR03	Shortlist	We have budget this year for an enterprise AI inventory and risk platform. Which vendors should our risk team evaluate first?
CR04	Shortlist	Our board wants oversight of every generative AI use case before we scale. Which AI governance platforms give a risk committee that view? Compare options.
CR05	Vendor selection	I am chief compliance officer at a global bank. Which AI governance product should we buy to evidence control over AI to regulators? Recommend specific products.
CR06	Vendor selection	We are issuing an RFP for an AI governance platform across risk, compliance and technology. Which vendors should we invite?
CR07	Requirements	Which AI governance tools build a complete inventory of AI models and generative AI use cases across a large bank, including third-party AI?
CR08	Requirements	Which platforms run risk tiering and impact assessments for each AI use case and route them for approval?
CR09	Requirements	Which AI governance products map controls to the EU AI Act, NIST AI RMF and ISO/IEC 42001 in one place?
CR10	Requirements	Which tools assess the AI risk of vendors and third-party software that embed AI, as part of third-party risk management?
CR11	Requirements	Which AI governance platforms keep an audit-ready record of approvals, assessments and changes for every AI system?
CR12	Validation	How do banks judge whether an AI governance platform will satisfy examiners, and which vendors have evidence of that?
CR13	Problem framing	How should a large bank set up governance for AI and generative AI without slowing delivery?
CR14	Problem framing	What does a mature AI risk management programme look like at a bank in 2026?

Model risk management lead (validation or second line, bank or insurer)

ID	Stage	Question
MR01	Shortlist	I run model risk management at a bank. Which platforms best support model risk management for both traditional models and generative AI? Compare them.
MR02	Shortlist	Which model risk management software do large banks use to comply with SR 11-7 style model risk guidance, and how do they compare?
MR03	Shortlist	We need to replace spreadsheets for our model inventory and validation workflow. Which vendors should we look at?
MR04	Shortlist	Which tools help a second-line model validation team validate large language model use cases? Give a shortlist with pros and cons.
MR05	Vendor selection	Which model risk management platform would you recommend for an insurer with 400 models across pricing, reserving and claims?
MR06	Vendor selection	Our model risk team needs one system for inventory, validation, monitoring and annual review. Which product should we buy?
MR07	Requirements	Which model risk tools manage validation findings, remediation and sign-off for each model?
MR08	Requirements	Which platforms monitor model performance and drift and feed the results into model risk reviews?
MR09	Requirements	Which tools calculate model risk tiers and schedule periodic revalidation automatically?
MR10	Requirements	Which model inventory products track model lineage, owners, versions and dependencies across business units?
MR11	Solution exploration	Which products help model validators test fairness, robustness and explainability of machine learning models?
MR12	Requirements	Which model risk platforms handle vendor models where we cannot see the code or training data?
MR13	Problem framing	How should model risk management change now that banks use generative AI?
MR14	Problem framing	What are the hardest parts of validating large language models for a bank's second line?

Head of AI or data science (enterprise ML and GenAI teams)

ID	Stage	Question
DS01	Shortlist	I lead AI and data science at a 10,000-person company. Which AI governance platforms work well for ML and GenAI teams without slowing them down? Compare them.
DS02	Shortlist	Which AI governance tools integrate best with ML platforms and model registries our data scientists already use?
DS03	Shortlist	We are scaling generative AI applications across business units. Which AI governance vendors should our AI platform team evaluate?
DS04	Shortlist	Which AI governance platforms include model monitoring, so our AI team does not need a separate tool?
DS05	Vendor selection	Which AI governance product would you recommend for a central AI team that must approve every model before production?
DS06	Vendor selection	Which AI governance platform should we buy to automate model documentation such as model cards for every release?
DS07	Requirements	Which tools turn our AI policy into automated checks in the model development workflow?
DS08	Requirements	Which AI governance platforms track which foundation models and prompts each generative AI application uses?
DS09	Requirements	Which tools generate risk assessments automatically from model metadata instead of long questionnaires?
DS10	Requirements	Which AI governance platforms sync automatically with cloud ML services so the AI inventory stays current?
DS11	Validation	How do AI teams measure whether a governance platform actually speeds up model approval? Which vendors publish results?
DS12	Requirements	Which tools collect evaluation and testing evidence for each model and attach it to the governance record?
DS13	Problem framing	How can a central AI team govern models and generative AI without becoming a bottleneck?
DS14	Problem framing	What should a head of AI put in place first to govern AI responsibly across a large company?

General counsel, legal or privacy lead

ID	Stage	Question
LG01	Shortlist	I am general counsel at a multinational. Which AI governance platforms help legal teams manage AI regulatory risk? Compare options.
LG02	Shortlist	Which AI governance tools are best for a legal and privacy team reviewing new generative AI use cases?
LG03	Shortlist	Our legal team wants a system to approve AI use cases and keep records of decisions. Which vendors should we consider?
LG04	Shortlist	Which privacy and AI governance platforms handle AI impact assessments alongside data protection impact assessments?
LG05	Vendor selection	Which AI governance product would you recommend for a legal department responsible for AI compliance across 30 countries?
LG06	Vendor selection	Which AI governance software should a company buy to track changing AI laws in different jurisdictions?
LG07	Requirements	Which tools keep a register of AI regulations and map each AI system to the obligations that apply?
LG08	Requirements	Which products help legal teams review AI terms and AI risk in vendor contracts?
LG09	Requirements	Which AI governance platforms record which employees use which generative AI tools and for what purpose?
LG10	Requirements	Which tools run AI impact and fundamental rights assessments with legal sign-off?
LG11	Solution exploration	Which products help prove compliance with AI transparency and disclosure rules?
LG12	Requirements	Which AI governance tools produce evidence packs for litigation or regulator inquiries about an AI system?
LG13	Problem framing	How should a legal team build an AI governance programme that keeps up with new laws?
LG14	Problem framing	What are the biggest legal risks of generative AI for a company, and how are they governed?

EU AI Act-driven European buyer (compliance or AI lead, EU organisation)

ID	Stage	Question
EU01	Shortlist	We are a German manufacturer preparing for the EU AI Act. Which AI governance platforms should we shortlist? Compare options.
EU02	Shortlist	Which AI governance tools best support EU AI Act compliance for high-risk AI systems, and why?
EU03	Shortlist	Which European AI governance vendors should an EU company consider for data sovereignty reasons?
EU04	Shortlist	Which AI governance platforms do European enterprises use for AI Act readiness, and how do they compare with US vendors?
EU05	Vendor selection	I am compliance lead at a French insurer. Which AI governance product should we buy to meet the EU AI Act and DORA together?
EU06	Vendor selection	Which AI governance software would you recommend for a Dutch company that must classify all its AI systems by EU AI Act risk level?
EU07	Requirements	Which tools produce the technical documentation and conformity evidence required for high-risk AI systems under the EU AI Act?
EU08	Requirements	Which AI governance platforms help deployers meet EU AI Act obligations for general-purpose AI models they use?
EU09	Requirements	Which AI governance tools host data in the EU and support GDPR as well as the AI Act?
EU10	Requirements	Which platforms support post-market monitoring and serious incident reporting under the EU AI Act?
EU11	Validation	How can an EU company check that an AI governance tool's EU AI Act mappings are accurate? Which vendors are credible here?
EU12	Requirements	Which AI governance products support reporting in languages other than English for European subsidiaries?
EU13	Problem framing	How are European companies preparing their AI governance for the EU AI Act?
EU14	Problem framing	What should an EU organisation do first to comply with the AI Act?

Healthcare or life sciences regulated buyer (compliance or clinical AI lead)

ID	Stage	Question
HC01	Shortlist	We are a hospital system using AI in clinical and administrative workflows. Which AI governance platforms suit healthcare? Compare options.
HC02	Shortlist	Which AI governance tools are strongest for assessing bias and safety in clinical AI models?
HC03	Shortlist	Which vendors should a health system evaluate to govern AI tools purchased from electronic health record and medical device vendors?
HC04	Shortlist	Which AI governance platforms do pharmaceutical companies use to validate and document AI models in regulated GxP processes?
HC05	Vendor selection	Which AI governance product should a US healthcare provider buy to document how its AI tools meet transparency and anti-discrimination rules?
HC06	Vendor selection	Which AI governance platform would you recommend for a medical device company managing AI models under quality and regulatory requirements?
HC07	Requirements	Which tools maintain an inventory of AI used across a health system, including AI embedded in purchased software?
HC08	Requirements	Which AI governance platforms monitor clinical AI models for performance drift across patient populations?
HC09	Requirements	Which AI governance tools help a life sciences company follow FDA and EMA guidance on AI in medical products and drug development?
HC10	Requirements	Which AI governance products can run without sending patient data outside our environment?
HC11	Solution exploration	Which products support an AI review committee in a hospital with intake, review and approval workflows?
HC12	Requirements	Which tools document health equity and bias assessments for each clinical AI tool?
HC13	Problem framing	How should a health system govern AI used in patient care?
HC14	Problem framing	What makes AI governance in healthcare different from other industries?

Public sector buyer (government agency CIO, CDO or AI lead)

ID	Stage	Question
PS01	Shortlist	We are a national government agency adopting AI across services. Which AI governance platforms suit the public sector? Compare options.
PS02	Shortlist	Which AI governance tools help a government publish and maintain a public register of its AI systems?
PS03	Shortlist	Which AI governance platforms give a city or state government an approval workflow for new AI uses, with public reporting built in?
PS04	Shortlist	Which AI governance platforms are best for meeting government AI policies on risk management and use case inventories?
PS05	Vendor selection	Which AI governance product would you recommend for a government agency that needs authorised cloud hosting such as FedRAMP?
PS06	Vendor selection	A ministry must buy an AI governance tool this year within a fixed budget. Which vendors should be on the tender list, and how are they priced?
PS07	Requirements	Which tools run algorithmic impact assessments for public services before an AI system goes live?
PS08	Requirements	Which AI governance platforms let an agency approve generative AI use cases for civil servants and publish what is approved?
PS09	Requirements	Which AI governance tools can be deployed on premises or in a sovereign government cloud?
PS10	Requirements	Which products help a government assess AI risk in software bought from suppliers?
PS11	Validation	How can a public agency verify that an AI governance platform supports transparency and accountability rules? Which vendors show evidence?
PS12	Requirements	Which AI governance tools keep records that support freedom of information requests and audits of AI decisions?
PS13	Problem framing	How should a government agency govern its use of AI to keep public trust?
PS14	Problem framing	What are governments doing to manage the risks of AI in public services?

Mid-market company adopting GenAI (CIO or COO, 300-3,000 staff)

ID	Stage	Question
MM01	Shortlist	We are a 1,000-person company rolling out generative AI tools. Which AI governance platforms suit a mid-sized business? Compare options.
MM02	Shortlist	Which AI governance tools are simple enough for a company without a dedicated AI risk team?
MM03	Shortlist	Which affordable AI governance vendors should a mid-market company look at this year?
MM04	Shortlist	What are the best AI governance platforms for a company that uses AI mainly through SaaS tools rather than building models?
MM05	Vendor selection	Which AI governance product would you recommend for a 2,000-employee company that needs an AI policy and inventory quickly?
MM06	Vendor selection	Which AI governance tool should a mid-sized SaaS company buy to answer customer questions about its AI use and certifications such as ISO/IEC 42001?
MM07	Requirements	Which tools discover which generative AI apps employees use and help us approve or block them?
MM08	Requirements	Which AI governance platforms provide ready-made AI policies, templates and training for staff?
MM09	Requirements	How much do AI governance platforms typically cost for a mid-sized company, and which vendors publish pricing?
MM10	Requirements	Which tools assess the AI features in the SaaS products we already buy?
MM11	Solution exploration	Which companies sell AI governance software, and what does it typically include?
MM12	Requirements	Which AI governance platforms can be set up in weeks without consultants?
MM13	Problem framing	How should a mid-sized company govern employee use of generative AI?
MM14	Problem framing	Does a mid-sized company need AI governance software, or are policies enough?

Appendix: 115 other vendors named

Filter vendors

Vendor	Table	ChatGPT r1 / r2	Gemini r1 / r2	Perplexity r1 / r2
2021.AI	Core	1 / 0	0 / 0	0 / 0
Airia	Core	3 / 1	0 / 0	4 / 5
Alation	Adjacent	0 / 0	0 / 1	2 / 3
Amazon (AWS)	Core	0 / 1	0 / 1	1 / 2
Aona	Core	1 / 1	1 / 2	0 / 0
Archer	Adjacent	1 / 5	5 / 3	1 / 2
Asenion	Core	2 / 2	0 / 0	0 / 0
Atlan	Adjacent	1 / 0	1 / 0	0 / 0
BigID	Core	0 / 0	0 / 0	2 / 2
BigID	Adjacent	0 / 0	3 / 1	2 / 4
Bitsight	Adjacent	1 / 1	1 / 0	1 / 1
Braintrust	Adjacent	0 / 2	4 / 1	4 / 3
Censinet	Adjacent	2 / 1	1 / 0	0 / 0
Check Point (incl. Lakera)	Adjacent	1 / 0	0 / 2	1 / 1
CIMCON	Core	0 / 1	3 / 0	2 / 2
Cisco (incl. Robust Intelligence)	Adjacent	2 / 1	2 / 1	1 / 0
Collibra	Core	2 / 2	1 / 2	3 / 4
Confident AI	Adjacent	2 / 2	1 / 1	5 / 3
CoreWeave (incl. Weights & Biases)	Adjacent	0 / 1	1 / 1	1 / 1
Cranium	Core	3 / 2	0 / 1	1 / 1
Darwin AI	Core	0 / 2	0 / 0	0 / 0
Datadog	Adjacent	0 / 0	0 / 3	0 / 0
DataGrail	Adjacent	1 / 0	0 / 1	1 / 1
DataGuard	Adjacent	0 / 2	1 / 0	0 / 0
Dataiku	Adjacent	1 / 2	4 / 4	4 / 5
DataRobot	Core	0 / 0	0 / 0	1 / 1
DataRobot	Adjacent	0 / 0	5 / 2	1 / 1
Decube	Adjacent	1 / 0	0 / 1	2 / 1
Deepchecks	Adjacent	0 / 1	1 / 1	1 / 1
Deeploy	Core	2 / 1	0 / 1	0 / 0
Diligent	Adjacent	1 / 1	0 / 0	1 / 1
Domino Data Lab	Core	0 / 0	1 / 1	0 / 0
Domino Data Lab	Adjacent	1 / 0	0 / 2	3 / 3
Enzai	Core	1 / 3	1 / 0	2 / 1
Euridium	Core	1 / 2	0 / 0	0 / 0
Evidently AI	Adjacent	0 / 1	1 / 1	1 / 0
EY	Adjacent	1 / 0	2 / 0	2 / 1
F5 (incl. CalypsoAI)	Adjacent	0 / 0	2 / 0	0 / 0
Fairlearn	Adjacent	2 / 3	2 / 1	2 / 2
Fairly AI	Core	1 / 3	1 / 1	2 / 0
FairNow	Core	1 / 2	3 / 2	4 / 3
Ferrum Health	Core	2 / 3	0 / 1	2 / 2
Galileo	Adjacent	0 / 0	2 / 5	4 / 2
Giskard	Adjacent	3 / 1	2 / 0	2 / 2
Google	Core	0 / 0	0 / 1	1 / 1
Govarna	Core	1 / 2	0 / 0	0 / 0
Govern365	Core	1 / 0	1 / 0	2 / 2
GOVERNBOX.ai	Core	2 / 1	0 / 0	0 / 0
H2O.ai	Adjacent	1 / 1	1 / 1	0 / 0
Harmonic Security	Adjacent	1 / 0	1 / 1	1 / 1
HiddenLayer	Adjacent	1 / 1	0 / 0	0 / 0
Hyperproof	Adjacent	0 / 0	3 / 1	0 / 0
ICRA Analytics	Core	3 / 1	0 / 0	0 / 0
Kertos	Adjacent	0 / 1	2 / 3	1 / 1
Kosmoy	Core	2 / 1	3 / 0	1 / 1
LangChain	Adjacent	1 / 1	3 / 3	1 / 1
Langfuse	Adjacent	1 / 2	0 / 3	2 / 2
Lasso Security	Adjacent	1 / 0	0 / 2	1 / 1
LatticeFlow AI	Core	1 / 0	0 / 0	2 / 2
LayerX	Adjacent	0 / 0	1 / 0	2 / 2
LegisGate	Core	2 / 2	0 / 0	0 / 0
Levenhall	Core	2 / 1	0 / 0	0 / 0
LogicGate	Adjacent	1 / 1	2 / 5	0 / 1
LucidTrust	Core	4 / 4	0 / 1	0 / 0
Lumenova AI	Core	0 / 0	2 / 1	2 / 0
MetricStream	Adjacent	0 / 0	6 / 6	1 / 2
Microsoft	Core	0 / 0	0 / 0	3 / 3
Mitratech	Adjacent	4 / 3	5 / 3	4 / 3
ModelValidation.ai	Core	0 / 2	0 / 0	1 / 1
Moody's	Core	0 / 1	0 / 0	0 / 0
Moody's	Adjacent	1 / 1	0 / 0	0 / 0
MRM Wiz	Core	2 / 0	0 / 1	0 / 0
Naaia	Core	1 / 1	0 / 1	0 / 0
Netskope	Adjacent	3 / 5	2 / 2	3 / 4
Nightfall AI	Adjacent	0 / 0	1 / 1	0 / 0
Noma Security	Adjacent	0 / 0	1 / 0	0 / 0
Norivo	Core	2 / 1	0 / 0	0 / 0
NVIDIA	Adjacent	4 / 3	1 / 1	1 / 0
Openlayer	Adjacent	1 / 3	5 / 5	5 / 4
OvalEdge	Adjacent	0 / 0	1 / 0	6 / 2
Pacific AI	Core	1 / 2	0 / 1	1 / 1
Palo Alto Networks (incl. Protect AI)	Adjacent	1 / 0	0 / 1	0 / 0
ProcessUnity	Adjacent	1 / 1	1 / 2	0 / 0
Productiv	Adjacent	0 / 1	0 / 1	1 / 1
Promptfoo	Adjacent	3 / 1	1 / 3	3 / 2
PwC	Adjacent	0 / 2	1 / 0	1 / 0
Ragas	Adjacent	1 / 0	0 / 0	2 / 2
Reco	Adjacent	0 / 0	2 / 3	2 / 3
Relyance AI	Adjacent	2 / 1	1 / 0	1 / 1
Riskonnect	Adjacent	0 / 0	0 / 1	0 / 1
Salesforce (incl. Informatica)	Adjacent	0 / 1	0 / 1	0 / 0
SAP	Adjacent	2 / 1	1 / 0	1 / 1
Secure Privacy	Adjacent	0 / 0	0 / 1	2 / 1
Secureframe	Adjacent	0 / 0	0 / 0	0 / 1
SecurityScorecard	Adjacent	0 / 1	1 / 1	0 / 0
SentinelOne (incl. Prompt Security)	Adjacent	1 / 1	1 / 1	0 / 0
SmartSuite	Core	0 / 0	0 / 0	1 / 2
Snowflake (incl. TruEra)	Adjacent	0 / 0	1 / 0	2 / 1
Sprinto	Adjacent	0 / 0	0 / 0	1 / 1
Thomson Reuters	Adjacent	0 / 0	1 / 0	0 / 0
Torii	Adjacent	1 / 2	0 / 1	1 / 2
TrustArc	Adjacent	1 / 2	3 / 4	1 / 1
Truyo	Core	2 / 1	0 / 1	2 / 2
UpGuard	Adjacent	0 / 0	4 / 3	2 / 3
VerifyWise	Core	1 / 2	0 / 1	4 / 4
Vitea	Core	2 / 3	0 / 0	0 / 0
Whistic	Adjacent	1 / 0	1 / 0	0 / 0
WhyLabs	Adjacent	1 / 1	1 / 1	3 / 3
WiseRegent	Core	1 / 1	0 / 0	0 / 0
WitnessAI	Adjacent	0 / 0	0 / 0	0 / 1
Wolters Kluwer	Adjacent	0 / 0	1 / 0	1 / 0
Yields	Core	0 / 0	4 / 4	6 / 6
Zenity	Adjacent	0 / 1	0 / 0	0 / 1
Zscaler	Adjacent	1 / 1	1 / 1	0 / 0
Zylo	Adjacent	1 / 1	1 / 1	0 / 0

FAQ

Where does my company rank?

Find it in Table 1 or Table 2 and use the row link to share its position. Then check the buyer-type and engine views, because a vendor's position often differs from one buyer type or engine to the next.

Why is my company missing?

It was named in fewer than 7 of the 112 questions in every engine run, or it was never named. Every vendor named at least once is in the appendix and the CSV with its exact figures.

How can a smaller vendor rank ahead of a larger one?

Because this measures how often AI engines name a vendor, not market share or deployments. A widely deployed product can be named rarely, and a smaller one can be named often. Both are accurate descriptions of what the engines said on the collection date.

Why do IBM, OneTrust and others appear in both tables?

Because the engines named them in both roles. OneTrust AI Governance counts as core, and OneTrust named for its privacy or third-party risk products counts as adjacent. Each table counts the company once per answer.

Why is AuditBoard not listed separately?

AuditBoard had been renamed Optro by the collection date, so its mentions count under Optro, with the label shown. Where one answer named both, it counts once.

Why are buyer-type scores higher than overall scores?

A buyer-type score is out of 84 answers (14 questions, six engine runs), and those questions are written for that buyer, so the relevant vendors appear more often. Compare buyer-type scores with each other and overall scores with each other, but not across the two.

Data and Citation

Download the vendor data (CSV) and the 112 questions (CSV). Both are free to reuse under CC BY 4.0 with credit to Ranking Atlas. Suggested citation: Ranking Atlas, AI Governance Software Vendor Visibility Index, October 2026 edition. Corrections and methodology questions: contact@ranking-atlas.com.