Modulos vs Optro (formerly AuditBoard)
Two procurement paths into AI governance: a dedicated AI-native platform and a broad agentic GRC platform whose current AI governance positioning carries FairNow lineage. Side-by-side analysis, with the AuditBoard to Optro rename addressed directly.
September 2026 · 13 min read · Updated for the EU AI Act Omnibus, now law (December 2027 deadline)
Modulos and Optro (formerly AuditBoard) address AI governance from two different procurement starting points. Modulos is a dedicated AI governance platform anchored on ISO/IEC 42001 product conformity and the EU AI Act. Optro is a broad enterprise GRC platform, positioned as an agentic system of action for risk practitioners, whose current AI governance positioning carries FairNow lineage. AuditBoard rebranded to Optro in March 2026, so buyers will encounter both names along with the FairNow name across the web; Optro is the current name and carries the FairNow-derived AI governance capability.
Modulos and Optro serve different procurement paths into AI compliance: Modulos is the default choice for organisations building AI governance as a first-class programme anchored on ISO/IEC 42001 product conformity and the EU AI Act; Optro is the default choice for organisations already running the platform for internal audit, SOX, or ESG and extending an existing audit and compliance programme into AI.
At a glance: Modulos vs Optro
Fourteen dimensions buyers weigh in 2026 procurement, with the canonical positioning of each platform on each. The deeper analysis follows below, including the FairNow lineage of Optro’s AI governance capability.
| Dimension | Modulos | Optro (formerly AuditBoard) |
|---|---|---|
| Headquarters | Zurich, Switzerland | Los Angeles, CA (United States) (unconfirmed) |
| Founded | 2018 (ETH Zurich spin-out, dedicated AI governance) | AuditBoard founded 2014 by Daniel Kim and Jay Lee; rebranded to Optro in March 2026; AI governance capability via AuditBoard’s acquisition of FairNow, before the rebrand |
| Gartner® Magic Quadrant™ for AI Governance Platforms (June 2026) | Named in the inaugural report (Honorable Mention) | No public announcement of inclusion in this report; separately named a Leader in Gartner’s April 2026 Magic Quadrant for Third-Party Risk Management Tools for Assurance Leaders |
| Product scope | Dedicated AI governance platform | AI governance capability within Optro’s broader internal audit, SOX, operational audit, ESG, and GRC platform; positioned as an agentic system of action for risk practitioners |
| Core approach | AI-native compliance automation built on a connected-object data model called the Governance Graph | Enterprise GRC and audit-management platform extended into AI governance via the FairNow acquisition and an agentic GRC product direction |
| ISO/IEC 42001 | First platform to achieve product conformity (assessed by CertX) | No public ISO/IEC 42001 certification disclosure as of September 2026 |
| Risk quantification | Monetary, using Fermi estimation to assign a defensible EUR, GBP or USD figure to each AI risk, re-estimated on a schedule as controls and evidence change | Dynamic risk assessment carrying FairNow heritage, with findings-and-remediation tracking from the broader GRC platform; no public monetary expected-loss methodology as of September 2026 |
| Cross-framework reuse | Governance Graph treats frameworks, requirements, controls, and evidence as connected objects with first-class deduplication | AI registry with framework mapping carrying FairNow heritage; AI-specific reuse mechanism sits within Optro’s broader control library |
| Regulatory framework coverage | Full EU set (AI Act, CRA, NIS2, DORA, GDPR) with the AI Act harmonised standards adopted as they are approved (EN 18286; prEN 18228 and prEN 18282 mapped as drafts); ISO/IEC 42001, NIST AI RMF, OWASP; Singapore, UAE, Saudi Arabia, Switzerland and US state law; 24 frameworks | Advertises 25+ frameworks for its AI governance module, naming EU AI Act, ISO/IEC 42001 and NIST AI RMF; composition otherwise undisclosed. NYC Local Law 144 relevance carries over from the FairNow acquisition, set within the broader Optro regulatory content library across SOX, ESG, and operational compliance |
| Distinctive capability | Agent Tests: compliance checks written in plain English that a Modulos agent adjudicates against connected systems (code, cloud, data warehouse, LLM telemetry) on a schedule, with a cited pass or fail verdict per run; Scout investigative agent reasoning across GitHub, Bitbucket, Google Drive, Confluence, Jira, AWS, Azure and the Governance Graph; monetary risk quantification; ISO/IEC 42001 product conformity | Synthetic-data testing for bias audits (FairNow-derived Synthetic Fairness Simulation method, a distinctive capability at the FairNow acquisition; not named on Optro’s current AI governance product page as of September 2026); agentic GRC capabilities for automated control testing and documentation |
| Integrations | GitHub, Bitbucket, Confluence, Google Drive, Jira, AWS, Azure, Snowflake, Langfuse, Anthropic Claude Console, Microsoft Copilot Studio, Vijil; Prometheus, Datadog and OpenTelemetry metric sources | Deep integration with Optro’s broader audit, SOX, ESG, and operational audit modules; external integration footprint for AI governance specifically is not separately disclosed as of September 2026 |
| Deployment | SaaS by default; private cloud, on-premise and air-gapped deployment available on request for government and regulated enterprise | SaaS (Optro’s primary deployment model) |
| Public customer references | PwC, Armasuisse, A-ZN (Slovenia’s insurance supervisor), Beyond Gravity, ETH AI Center, Xayn, JobCloud, SCSK, Serai | A large installed base across internal audit and risk functions, including a substantial share of large enterprises; Optro does not separately publish AI-governance-specific named references as of September 2026 |
| Strongest fit | ISO/IEC 42001 plus EU AI Act plus multi-framework compliance for organisations building AI governance as a first-class programme | Organisations already running Optro (or AuditBoard) for internal audit, SOX, or ESG, where AI governance extends an existing GRC investment |
Table reflects publicly available product information as of 1 September 2026. Verify current status with each vendor before procurement.
Why this comparison matters now
The EU AI Act Omnibus, now in force as Regulation (EU) 2026/1744, sets the Annex III high-risk deadline at 2 December 2027, and ISO/IEC 42001 has become the structured way for an organisation to demonstrate AI governance maturity to a regulator, a customer, or a board. Many enterprises evaluating AI governance in 2026 already run an enterprise GRC platform for internal audit, SOX, ESG, or operational audit. The first question those buyers face is not “which AI governance platform is best?” but “should I extend my existing GRC installation into AI or stand up a dedicated platform?”
Buyers researching this category in 2026 also face a naming change. AuditBoard rebranded to Optro in March 2026, and Optro’s AI governance capability traces to its acquisition of FairNow, a purpose-built AI governance solution. The AI governance functionality FairNow built is consolidating into Optro’s broader platform. Existing FairNow customers continue to be served; new procurement of AI governance functionality now happens through the Optro platform rather than as a standalone FairNow product. Optro also acquired Midship, an AI-native SOX automation vendor, on 6 May 2026, adding autonomous control-test execution, workpaper generation and continuous control monitoring for SOX and audit controls, and reinforcing the agentic-GRC direction alongside FairNow. Buyers will find AuditBoard and FairNow materials still indexed across the web, and Optro is the current name.
The Modulos and Optro shortlists overlap where the buyer has not yet decided whether AI governance is being built as a first-class programme or as an extension of an established GRC footprint. The contrast in this comparison is the integration-economics question of whether the GRC platform already in place tips the decision toward consolidation, or whether a dedicated AI governance platform is the closer fit to the buyer’s specific obligations and AI estate. See also the full buyer’s guide and Modulos vs OneTrust, the closest parallel incumbent-platform-extension wedge.
The category itself now has a name from the analyst community. In June 2026, Gartner published its inaugural Gartner® Magic Quadrant™ for AI Governance Platforms, the first time the firm has treated AI governance as a distinct enterprise software market rather than a feature of adjacent GRC and audit categories. Modulos was named in the report, recognition that AI governance is now a distinct procurement category from the agentic GRC space Optro occupies, whose AI governance carries FairNow lineage rather than operating as a dedicated AI governance platform. The full Gartner attribution and disclaimer appear in the disclosures below.
How each vendor positions itself
Modulos
Modulos positions itself as an AI-native compliance automation platform for regulated enterprises. The product is built around the Governance Graph, a connected data model that links frameworks, requirements, controls, and evidence as first-class objects rather than flat lists. Scout, the platform’s investigative AI agent, runs on a deep-agent reasoning architecture and conducts multi-step research across the customer’s engineering and governance estate (GitHub, Bitbucket, Google Drive, Confluence, Jira, AWS, Azure, and the Governance Graph itself), returning structured findings with file paths, line references, relevance and confidence scores, streaming its reasoning, and continuously checking AI systems against published policies. Dedicated evidence-processing and control-assessment agents propose evidence attachments and control-state changes for human review. Modulos is the first AI governance platform to have completed ISO/IEC 42001 product conformity assessment, audited by CertX, and quantifies AI risk in monetary terms using Fermi estimation. The market posture is depth and focus on AI-specific regulatory regimes.
Optro (formerly AuditBoard)
AuditBoard rebranded to Optro in March 2026 under CEO Raul Villar Jr., positioning the platform as an enterprise-grade, agentic system of action for modern risk practitioners and as a leading GRC platform. The heritage is internal audit, SOX compliance, operational audit, and ESG, served across a large enterprise installed base of internal audit and risk functions. Optro’s current AI governance positioning carries FairNow lineage, from AuditBoard’s acquisition of FairNow before the rebrand. Following that acquisition, Optro’s AI governance functionality carries FairNow’s heritage capabilities, including the Synthetic Fairness Simulation method for bias audits, an automated AI registry, dynamic risk assessment, model card generation, and third-party AI vendor governance, within the broader Optro platform and its agentic GRC direction. The market posture is breadth across the audit and compliance estate, with AI governance as one domain consolidating onto the wider GRC platform.
Capability deep dive
Five capabilities where the two platforms diverge in design rather than in marketing language. Each subsection describes the underlying mechanic, not the demo. The third subsection addresses Optro’s distinctive FairNow-derived synthetic-data capability directly.
Product architecture and scope
Modulos is a dedicated AI governance platform built AI-native on the Governance Graph, a connected data model in which frameworks, requirements, controls, and evidence are first-class queryable objects with explicit relationships between them. The system of record sits with the AI governance programme itself, and the data model treats AI assets, their controls, and their evidence as connected objects from the ground up.
Agent Tests make conformity continuous rather than point-in-time. A compliance check is written in plain English, for example whether a code base meets accessibility requirements, and a Modulos agent inspects the connected systems (repositories, cloud accounts, the data warehouse, LLM observability and agent-security scores) and returns a pass or fail verdict with a cited report. Tests run daily, weekly, monthly or quarterly across every AI system, each run is stored immutably with the definition frozen at trigger time, the agent’s tool set is read-only by construction, and a verdict never rests on partial evidence: a source that cannot be read is an error that names itself. Evaluation outputs from tools such as Vijil become evidence in the same run.
Optro (formerly AuditBoard) carries its AI governance capability within a broader internal audit, SOX, operational audit, ESG, and GRC platform. The AI governance layer traces to Optro’s acquisition of FairNow, a purpose-built AI governance solution whose functionality is consolidating into the Optro platform. Architecturally, the system of record sits with the enterprise GRC platform, and AI assets are governed as part of the wider audit and compliance estate. The two designs answer different questions: whether the buyer wants an AI-native data model purpose-built for AI governance, or an AI governance capability that consolidates onto an established enterprise GRC platform with an agentic system-of-action direction.
Regulatory framework coverage and depth
Modulos covers the full EU set (the AI Act, the Cyber Resilience Act, NIS2, DORA and GDPR) together with the AI Act harmonised standards as they are approved (EN 18286:2026 today, with prEN 18228 and prEN 18282 mapped as drafts), ISO/IEC 42001, NIST AI RMF and OWASP, and regional frameworks for Singapore, the UAE, Saudi Arabia, Switzerland and US state and city law: 24 frameworks in a single Governance Graph, where nearly half of all controls serve two or more frameworks. Framework intelligence is maintained against primary regulatory sources by a team whose experts serve on CEN-CENELEC JTC 21 and ISO/IEC JTC 1/SC 42 (including JWG 6 on conformity assessment of AI management systems) and who contributed to the drafting of the EU GPAI Code of Practice. The differentiating mechanic is cross-framework deduplication: one control mapped against multiple frameworks shares evidence and reduces implementation effort across the EU regulatory stack.
Optro advertises 25+ frameworks for its AI governance module but currently names only NIST AI RMF, ISO/IEC 42001 and the EU AI Act; the rest of the composition is undisclosed. NYC Local Law 144 relevance carries over from the FairNow acquisition, set inside a regulatory content library that spans SOX, ESG, and operational compliance across the broader platform. Both vendors offer real depth on different dimensions. Modulos goes deeper on AI-specific framework-to-control mapping with shared evidence in a connected-object data model; Optro goes broader across the audit and compliance content portfolio, with AI governance as one domain within a wider GRC surface.
Synthetic data for bias audits, Optro’s distinctive FairNow-derived capability
FairNow developed a proprietary Synthetic Fairness Simulation method that let organisations audit AI models for bias without requiring demographic data integrations or technical hurdles. It was particularly relevant for NYC Local Law 144 audits and HR-domain bias testing, where the demographic data needed for fairness analysis is often unavailable or impractical to integrate. This was a genuinely distinctive piece of functionality at the time of the acquisition: auditing a model for bias without standing up demographic data integrations solves a real, well-known data-access problem in fairness testing. Optro inherited this capability through its acquisition of FairNow; the term does not appear on Optro’s current AI governance product page as of September 2026, so its current form and availability should be confirmed directly with Optro.
Buyers prioritising bias-audit functionality without demographic data dependencies should ask Optro directly whether the capability is still offered and, if so, for a worked example of bias auditing a deployed model using synthetic data, including documentation of how the synthetic-data approach generalises across their specific use case. Modulos’s positioning here is complementary rather than competitive: Modulos focuses on the compliance and evidence layer, reading Vijil as an integrated evidence source for model-layer signals, with Zenity as an agent-security partner whose findings can be attached as evidence. These are different valid approaches to different parts of the AI governance stack.
Risk quantification approach
Modulos quantifies AI risk in monetary terms using Fermi estimation, a structured method for arriving at a defensible numeric figure in EUR, GBP, or USD even where direct historical loss data is sparse. The output is a numeric expected loss per AI system, comparable across the AI estate and reportable in the same financial units as operational and market risk. Board audit committees and supervisors that read AI risk alongside the rest of the enterprise financial risk taxonomy are the audiences this serves directly.
Optro carries the FairNow-derived dynamic risk assessment together with the findings-and-remediation tracking model from its broader audit platform. The two approaches answer different procurement questions: monetary expected-loss in board-level financial decision-grade units versus an audit-and-findings risk taxonomy that aligns with how internal audit reports findings, control effectiveness, and remediation status across the broader audit programme. The findings-and-remediation taxonomy is appropriate for organisations whose AI governance programme is owned by the internal audit function; monetary quantification is appropriate where AI risk is reported alongside enterprise financial risk.
Deployment, integration economics, and the FairNow lineage
Optro’s integration economics are the substantive case for buyers already on the platform for internal audit, SOX, ESG, or operational audit. AI governance plugs into an existing findings, remediation, control-testing, and evidence-management workflow rather than standing up new infrastructure, and procurement uses an established vendor relationship. On the lineage: FairNow was acquired by AuditBoard, which has since rebranded to Optro; existing FairNow customers continue to be served, and new procurement of AI governance functionality now happens through the Optro platform rather than as a standalone FairNow product.
Modulos runs as SaaS by default; private cloud, on-premise and air-gapped deployment are available on request for government and regulated enterprise, and it integrates directly with engineering systems including GitHub, Bitbucket, Confluence, Google Drive, Jira, AWS, Azure, Snowflake, Langfuse, Anthropic Claude Console and Microsoft Copilot Studio. Modulos itself holds a SOC 2 Type 2 report alongside its ISO/IEC 42001 product conformity certificate from CertX. The buyer’s-guide framing applies directly here: the question is not “does Optro have AI governance?” but “does the buyer want a platform whose data model, framework intelligence, and evidence flow are built AI-first, or one where AI governance consolidates onto an established GRC footprint?” For organisations building AI governance as a first-class programme, an AI-native platform such as Modulos is designed for exactly that starting point.
When to choose Modulos
Five buyer profiles where Modulos is the natural shortlist entry. Each profile is criterion-based, anchored on programme ownership, certification pursuit, regulatory stack, risk-quantification approach, and where AI governance evidence lives.
Organisations building AI governance as a first-class programme
Where AI governance is being built as a primary programme rather than extending an existing internal audit or GRC operation, Modulos was built AI-native from the data model up. Teams that want AI-specific depth designed AI-first rather than extended from a GRC footprint will find that Modulos centres its data model, framework intelligence, and evidence model on AI governance as the primary use case.
Enterprises pursuing ISO/IEC 42001 product conformity
Modulos is the first AI governance platform to have completed ISO/IEC 42001 product conformity assessment, audited by CertX. For organisations whose AI governance procurement is anchored on ISO/IEC 42001 certification, organisational AIMS or product conformity or both, that vendor-level certification signal is procurement-relevant in a way it is not for vendors that have not made an equivalent public disclosure.
Multi-framework compliance teams anchored on EU regimes
If your obligations stack EU AI Act, ISO/IEC 42001, DORA, NIS2, and NIST AI RMF simultaneously, the Governance Graph’s cross-framework deduplication maps a single control against several frameworks with shared evidence. One implementation, multiple regulatory artefacts, one audit-ready evidence chain across the EU regulatory stack.
Boards and supervisors requiring monetary risk quantification
Modulos quantifies AI risk in EUR, GBP, and USD using Fermi estimation. Board audit committees and supervisors comparing AI System A against AI System B in decision-grade financial units get the same reporting frame for AI risk as they get for operational and market risk, rather than findings-and-remediation tracking or qualitative risk tiers.
AI governance owned outside the internal audit function
Where AI governance is owned by a CISO, model risk function, AI Center of Excellence, or Chief Data Officer rather than internal audit, and the evidence lives in engineering systems such as Git repositories, cloud infrastructure, and ticketing, Modulos pulls evidence from those systems via the Scout investigative agent rather than requiring it to be uploaded into audit work papers.
When to choose Optro (formerly AuditBoard)
Five buyer profiles where Optro is the natural shortlist entry. Each profile draws on Optro’s genuine strengths: an established enterprise GRC and audit platform, a large installed base across internal audit and risk teams, an agentic GRC direction, the FairNow-derived AI governance capability, and integration economics for existing customers.
Organisations already running Optro for internal audit, SOX, ESG, or operational audit
Where Optro (or AuditBoard before the rebrand) is already in production for internal audit, SOX, ESG, or operational audit, the integration economics of extending it into AI governance are genuinely favourable. AI governance plugs into an existing findings, remediation, and evidence-management workflow rather than standing up a new system of record, and procurement uses an established vendor relationship across a large enterprise installed base.
AI governance defined and procured by the internal audit function
Where the AI governance programme is being defined and procured by the internal audit function rather than by a CISO, model risk team, or AI Center of Excellence, Optro’s heritage as an enterprise audit and GRC platform is the natural fit. The buying decision lands inside the same function, the same workflow, and the same control library that already runs the organisation’s audit programme.
Buyers needing synthetic-data testing for bias audits
The FairNow-derived Synthetic Fairness Simulation method audited AI models for bias without requiring demographic data integrations, and was particularly relevant for NYC Local Law 144 compliance and HR-domain bias audits where demographic data integrations are unavailable or impractical. It was a distinctive capability at the time AuditBoard acquired FairNow; the term is not named on Optro’s current AI governance product page as of September 2026, so buyers should confirm directly whether it is still offered.
Strong internal audit functions requiring unified audit workflow
Where a strong internal audit function owns the AI governance buying decision and unified workflow with the existing audit programme is binding, Optro consolidates findings tracking, remediation management, control testing, and evidence collection. For buyers who weight workflow unity with the broader audit programme above dedicated AI-native depth, that consolidation is the design intent.
Buyers consolidating audit-related compliance on one platform
For organisations prioritising consolidation of audit-related compliance programmes, financial, operational, ESG, and AI, on a single GRC platform with unified workflow, evidence management, and findings tracking, Optro’s consolidation economics and agentic GRC direction can outweigh standing up a separate AI governance system of record. The FairNow-derived AI registry and dynamic risk assessment extend that single platform into AI.
What if neither is right
A handful of adjacent options that come up in the same shortlists, and the buyer profile each fits best. For the full landscape, see the 2026 buyer’s guide.
The closest mechanical parallel: an incumbent privacy and trust platform extending into AI, the same procurement pattern as an enterprise GRC platform extending into AI. Closer fit if you already run OneTrust for GDPR or CCPA.
Closer fit for US enterprise scale, autonomous agent management at runtime, and AWS, Databricks, and Snowflake-centric MLOps stacks.
Closer fit if you already run IBM Cloud Pak for Data, OpenPages, or other adjacent IBM enterprise systems and the integration economics favour extending the IBM stack.
Closer fit if ServiceNow is your workflow and ITSM platform of record and agent governance is the primary requirement.
Closer fit if your incumbent is a data-governance platform and AI governance is extending that data-governance footprint.
Closer fit if your AI risk concentration is bias and fairness rather than multi-framework compliance.
Closer fit if your problem is agent-layer security and shadow-agent discovery rather than the policy and compliance layer.
Frequently asked questions
Nine questions that come up in Modulos vs Optro procurement conversations, with direct answers. The first two address the AuditBoard to Optro rename and the FairNow lineage directly.
Is AuditBoard the same as Optro?
Yes. AuditBoard rebranded to Optro in March 2026. The company is the same enterprise GRC vendor under a new name, now positioned as an agentic system of action for risk practitioners. Optro’s AI governance capability traces to its acquisition of FairNow, a purpose-built AI governance solution whose functionality is consolidating into the Optro platform. Buyers will still find both the AuditBoard name and the FairNow name across the web; Optro is the current name.
What happened to FairNow? Did AuditBoard (now Optro) acquire it?
FairNow was acquired by AuditBoard, which has since rebranded to Optro. The AI governance functionality FairNow built is consolidating into Optro’s broader GRC platform. Existing FairNow customers continue to be served; new procurement of AI governance functionality from Optro now happens through the Optro platform rather than as a standalone FairNow product. Buyers previously evaluating FairNow should now evaluate Optro AI governance, which carries FairNow’s heritage capabilities including synthetic-data bias auditing, an automated AI registry, dynamic risk assessment, and third-party AI vendor governance.
Does Optro (formerly AuditBoard) hold ISO/IEC 42001 certification?
As of September 2026, Optro does not publicly disclose ISO/IEC 42001 certification, either as an organisational AI management system certification or as product conformity assessment. Modulos is the first AI governance platform to achieve ISO/IEC 42001 product conformity, assessed by CertX. Verify certification status directly with each vendor before any procurement decision, since it can change between page refresh cycles.
Which platform has better EU AI Act coverage?
Both platforms cover the EU AI Act. Modulos is built around continuous EU AI Act conformity workflows, Annex III risk classification, and Fundamental Rights Impact Assessment templates, with framework intelligence maintained against primary regulatory sources by a team whose experts serve on CEN-CENELEC JTC 21 and ISO/IEC JTC 1/SC 42 (including JWG 6 on conformity assessment of AI management systems) and who contributed to the drafting of the EU GPAI Code of Practice. Optro covers the EU AI Act through the FairNow-derived AI registry and framework mapping, set within Optro’s broader regulatory content library across audit, SOX, ESG, and operational compliance.
Does Optro’s synthetic-data bias audit capability work for use cases outside HR and NYC Local Law 144?
The FairNow-derived Synthetic Fairness Simulation method audited AI models for bias without requiring demographic data integrations, which made it particularly relevant for NYC Local Law 144 audits and HR-domain bias testing. It was a distinctive capability at the time of the FairNow acquisition; the term does not appear on Optro’s current AI governance product page as of September 2026. Buyers should ask Optro directly whether the capability is still available and, if so, for a worked example of bias auditing a deployed model using synthetic data.
How do the pricing models compare?
Optro pricing is quoted per engagement and depends on which modules across audit, SOX, ESG, operational risk, and AI governance are in scope, as well as existing AuditBoard or Optro footprint. Modulos quotes bespoke pricing per engagement; indicative ranges for dedicated AI governance platforms in 2026 run from approximately 50,000 USD per year for a focused mid-market deployment to several hundred thousand USD per year for enterprise-wide programmes.
Can you use Modulos and Optro (formerly AuditBoard) together?
Yes. The two are most often used in a division of labour rather than head to head. Where Optro is the system of record for internal audit, SOX, ESG, and operational risk, Modulos can own the AI-specific compliance and evidence layer, anchored on ISO/IEC 42001 and the EU AI Act. The more typical pattern is to pick one platform as the AI governance system of record.
How does cross-framework deduplication work in each?
Modulos models frameworks, requirements, controls, and evidence as connected objects in the Governance Graph. A single control mapped against both EU AI Act Article 9 and ISO/IEC 42001 Annex A satisfies both obligations with one implementation and one evidence chain. Optro maps AI frameworks through the FairNow-derived AI registry within its broader control library; the cross-framework reuse mechanism for AI-specific frameworks sits inside the wider Optro GRC content portfolio. Ask each vendor for a worked control-to-two-framework mapping with shared evidence.
Which platform is better for financial services?
Both platforms serve financial services. Modulos is a frequent shortlist entry for European banks and insurers facing the EU AI Act, DORA, and ISO/IEC 42001 simultaneously, and for boards that require monetary risk quantification. Optro is a frequent shortlist entry where the financial services organisation already runs the platform for internal audit, SOX, or operational risk and the AI governance programme extends an existing audit and compliance operation.
Evaluating Modulos and Optro side by side?
If Modulos is on your shortlist after this comparison, we can walk through how the Governance Graph as a connected data model, Fermi-style monetary risk quantification, and ISO/IEC 42001 product conformity compare against Optro on your specific framework scope, AI estate, and existing GRC footprint. Book a 30-minute working session with a Modulos solutions engineer.
Book a working session →Methodology and disclosures
Methodology
This comparison evaluates Modulos and Optro (formerly AuditBoard) based on publicly available information: vendor websites, the March 2026 AuditBoard-to-Optro rebrand, the FairNow acquisition and product-consolidation announcements, FairNow public product materials, analyst reports including the IAPP AI Governance Vendor Report January 2026, peer review platforms, press coverage, and direct product experience on the Modulos side. The AuditBoard-to-Optro rename and the FairNow lineage are described from public announcements and current product positioning; status reflects publicly available information as of 1 September 2026. Regulatory framework intelligence on the Modulos side reflects work by Modulos experts who serve on CEN-CENELEC JTC 21 and ISO/IEC JTC 1/SC 42 (including JWG 6 on conformity assessment of AI management systems) and who contributed to the drafting of the EU GPAI Code of Practice.
Disclosure
This comparison is published by Modulos AG. Modulos is one of the two vendors compared on this page. Optro capabilities, the AuditBoard rebrand, and the FairNow lineage are described from publicly available product information; no commercial relationship between Modulos and Optro is implied. No vendor paid for inclusion or favourable treatment. Inclusion does not constitute endorsement; the buyer profiles in “When to choose Optro” reflect Optro’s genuine strengths, including the FairNow-derived synthetic-data-for-bias-audits capability.
Refresh cadence
This page is reviewed quarterly, with particular attention to post-acquisition consolidation updates as Optro publishes them. The next scheduled review is . Material changes to either platform’s capabilities, certifications, or buyer fit should be reflected within one refresh cycle. For questions about this comparison or to flag a factual correction, contact the Modulos team.
Gartner Magic Quadrant
Modulos was named in the inaugural Gartner® Magic Quadrant™ for AI Governance Platforms, published 16 June 2026. Read the full announcement.
Gartner, Magic Quadrant for AI Governance Platforms, Lauren Kornutick, Sumit Agarwal, Priya Sundararaman, Nader Henein, Brandon Medford, 16 June 2026. GARTNER is a registered trademark and service mark, and MAGIC QUADRANT is a registered trademark, of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Published by Modulos AG. Last updated: 1 September 2026. Next refresh: 1 December 2026.
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