These are the best tools if you are looking to comply with the EU AI Act in companies:
- PrivaLex
- OneTrust
- Credo AI
- Holistic AI
- IBM watsonx.governance
- Microsoft Purview
- ServiceNow
- Securiti
Searching for the best tools for EU AI Act compliance in companies usually means the team already faces real pressure: customers asking for evidence, committees asking about generative AI, vendors embedding models or business units deploying tools without a formal approval process.
The right tool is not always the best-known one. The European Commission’s AI Act framework requires companies to look at AI by risk level, provider or deployer role, transparency, documentation, human oversight and specific controls for high-risk systems. A company therefore needs a solution that helps operate inventory, classification, evidence, vendors and continuous review, not just a policy repository.
The 8 best tools for EU AI Act compliance in companies
1. PrivaLex
PrivaLex is not a SaaS tool, but it should appear first when a company is looking for software for EU AI Act compliance because tool selection depends on the compliance model behind it. Before choosing OneTrust, Credo AI, Holistic AI, IBM, Microsoft, ServiceNow or Securiti, the company should define which AI systems exist, what risks they create, what evidence must be retained and who will operate the programme.
In AI Act projects, PrivaLex helps turn regulatory requirements into purchasing and configuration criteria: inventory, risk classification, controls, workflows, vendors, evidence and reporting. This prevents companies from buying a powerful platform that is poorly configured, or a specialist tool that does not integrate with privacy, security or corporate GRC.
PrivaLex fits if you need:
- Functional requirements before buying software.
- Tool comparison from a compliance perspective, not only features.
- Configuration of an existing platform for the AI Act, GDPR and ISO 42001.
- Evidence for enterprise customers, audit or management.
- Alignment across legal, product, security, compliance and procurement.
The right tool can accelerate compliance. But if the company does not know what it must prove, which controls it needs or what data feeds its AI systems, software becomes another layer of confusion.
2. OneTrust
OneTrust is one of the strongest options if the company already manages privacy, third parties, data governance or compliance inside a corporate suite. According to the official OneTrust AI Governance page, the platform supports AI system cataloguing, risk assessment, EU AI Act, NIST and ISO 42001 templates, workflow automation and audit evidence.
Its natural fit is in organisations where AI and privacy are closely connected: SaaS tools with personal data, cloud providers, records of processing, impact assessments and compliance reporting. It can also make sense if the company already uses OneTrust for GDPR or third-party management and wants to extend the stack before introducing another tool.
OneTrust fits if you need:
- Inventory of models, agents, datasets and vendors.
- Review workflows for new AI use cases.
- Connection between AI governance, privacy and third-party risk.
- Auditable evidence for management, customers and internal audit.
- A broad solution for mature compliance teams.
The caution is complexity. If the team does not yet know which AI systems it has, who approves them or how risk is classified, design the governance model first. A large suite does not fix a missing process by itself.
3. Credo AI
Credo AI is specifically focused on AI governance. The official Credo AI site places it in the AI governance space, making it interesting for companies that want a specialist layer for policies, assessments, reviews and evidence around AI systems.
Its strength is that it starts from the specific problem of governing AI, rather than from generic GRC. It can help when there are many use cases in product, operations, marketing, HR or customer support and the company needs a consistent way to assess and approve systems before they scale.
Credo AI fits if you need:
- A live AI systems register.
- Policies and assessments specific to AI.
- Coordination between legal, compliance, data science and product.
- Traceability of decisions and approvals.
- Governance evidence for enterprise customers or internal audits.
Before choosing it, review integration. If you already have GRC, privacy, security or MLOps, the tool must connect with that map. Otherwise it may become another parallel repository.
4. Holistic AI
Holistic AI can fit when the company needs more technical depth in risk assessment: bias, fairness, robustness, explainability, documentation, assurance and model controls. The official Holistic AI page positions the tool around AI governance and assurance.
This approach is especially useful for systems affecting people or sensitive decisions: hiring, credit, insurance, education, health, public services or access to essential services. For the AI Act, having a policy is not enough; the company must demonstrate testing, human review, traceability and mitigation measures.
Holistic AI fits if you need:
- Technical assessments of models or systems.
- Evidence on bias, fairness, robustness or explainability.
- Assurance documentation for internal teams or third parties.
- Support for use cases affecting fundamental rights.
- A specialist layer that complements GRC or privacy.
It will not always be the main compliance system. In many companies, it works best as a technical layer connected to a broader GRC, privacy and risk management programme.
5. IBM watsonx.governance
IBM watsonx.governance is a strong option for large companies, hybrid environments and complex AI ecosystems. IBM describes watsonx.governance as a solution for AI governance, risk and compliance, with visibility, control, accountability and audit-ready reporting.
It can fit when the organisation needs to connect AI assets, policies, risks, controls and metrics across a broad environment. It may also make sense in regulated sectors where AI governance must coexist with operational risk, continuity, third parties and corporate compliance.
IBM watsonx.governance fits if you need:
- Visibility over many AI assets.
- Links between policies, risks, controls and systems.
- Reporting for audit, management or global risk functions.
- Integration with complex corporate ecosystems.
- Continuous control over production systems.
The trade-off is the maturity required. It is usually not the first choice for small teams that only need inventory and a control matrix. It requires architecture, internal governance and implementation capacity.
6. Microsoft Purview
Microsoft Purview can be useful if the company already lives inside the Microsoft ecosystem and wants to connect compliance, data, security and identities with its AI programme. Purview Compliance Manager focuses on compliance management, control assessment and compliance posture improvement.
For the AI Act, Purview should not be seen as a complete solution by itself. Its value sits in the data and compliance layer: information classification, protection, eDiscovery, retention, permissions and controls over sensitive data. Many AI risks start exactly there.
Microsoft Purview fits if you need:
- Data governance inside the Microsoft stack.
- Controls over sensitive information used in AI processes.
- Links between compliance, security and identities.
- Compliance evidence for teams already using Microsoft 365 or Azure.
- A data and security base that complements AI governance.
If the main problem is classifying AI systems by risk, documenting human oversight or preparing ISO 42001, Purview will need to be complemented with consulting or a more specific AI governance layer.
7. ServiceNow
ServiceNow fits when the company already manages risk, compliance, workflows, incidents and corporate operations inside that platform. The ServiceNow GRC page focuses on connecting risk, controls, audit and compliance in business processes.
For companies with mature corporate GRC, extending ServiceNow to AI may be more efficient than buying an isolated tool. It allows teams to assign tasks, review exceptions, manage evidence, escalate incidents and report to committees inside an environment they already know.
ServiceNow fits if you need:
- AI integrated into the corporate risk programme.
- Approval, review and incident workflows.
- AI controls connected with internal audit, security and vendors.
- Avoiding a separate tool for every regulatory framework.
- Reporting scaled to management and risk committees.
The limit is that corporate GRC does not always capture AI-specific features well: models, datasets, prompts, substantial changes, human oversight or performance metrics. If you choose this route, design an AI-specific taxonomy.
8. Securiti
Securiti can be relevant when the main risk sits in data, privacy, data intelligence and compliance automation. Its official AI Governance page presents capabilities for discovering, cataloguing and governing AI systems, with a focus on risk, data and compliance.
It can fit companies where AI systems depend on large volumes of personal data, sensitive information, multi-cloud environments or many vendors. In those cases, AI Act compliance overlaps with GDPR, data discovery, data classification, data subject rights and transfers.
Securiti fits if you need:
- Discovery of AI systems and related data flows.
- AI governance connected with privacy and data intelligence.
- Management of personal data risks in AI systems.
- Visibility in multi-cloud or complex environments.
- Integration of AI compliance with global privacy programmes.
It does not replace legal judgement or governance design by itself. It can be a powerful piece when the main exposure sits in data and privacy.
What problem each type of tool solves
Not every AI Act tool solves the same problem. Some are strong in privacy, others in corporate GRC, others in technical assurance and others in AI-specific governance. Before buying, decide which layer the company needs to strengthen.
- AI governance. Tools such as Credo AI or Holistic AI help structure policies, assessments, reviews and evidence for AI systems.
- Corporate GRC and compliance. OneTrust, ServiceNow or IBM can fit when the goal is to integrate AI into risk, controls, audit and enterprise reporting.
- Privacy and data. Microsoft Purview and Securiti are relevant when the main risk sits in personal data, classification, access, retention or multi-cloud flows.
- Programme design. PrivaLex fits before, during and after technology selection, defining what the tool must prove and how it connects with the AI Act, GDPR, ISO 42001 and B2B customers.
Buying matrix for companies
Before requesting demos, the company should answer these questions precisely:
- Which AI systems we have. Include proprietary models, SaaS tools with AI, agents, copilots, scoring, automations and product integrations.
- Which data they use. Personal data, sensitive data, confidential information, training data, prompts, logs and outputs.
- Which role we play. Provider, deployer, integrator, software buyer, internal user or several at once.
- Which evidence we need. Approvals, tests, human reviews, vendor assessments, minutes, logs, policies and controls.
- Which tools already exist. Corporate GRC, DPO tooling, ticketing, MLOps, cloud security, IAM, data catalogue or Microsoft suite.
- Who will operate the system. Legal, compliance, security, product, data, procurement, internal audit or a cross-functional committee.
If you cannot answer these questions, vendor demos will look attractive but remain hard to act on.
Implementation plan in 30, 60 and 90 days
A practical way to avoid poorly focused purchases is to split implementation into phases.
First 30 days. Create the initial inventory, identify critical systems, list vendors, detect personal data and appoint internal owners. PrivaLex can help set scope and criteria before the tool is configured.
Days 31 to 60. Classify risks, define minimum controls, document approval workflows, map evidence and decide which part will be operated in the tool. Avoid overconfiguration nobody will maintain.
Days 61 to 90. Test the flow with real use cases, prepare management reporting, create customer evidence packs and adjust periodic review. If the company targets ISO 42001, this is where the tool starts connecting with management system scope, objectives and continual improvement.
Internal roles that should participate
EU AI Act compliance does not belong only to legal or only to IT. A useful tool should let several teams participate without duplicating work.
- Legal and compliance define obligations, risk criteria and regulatory evidence.
- Privacy or DPO reviews personal data, information to individuals, DPIAs and rights.
- Security evaluates access, vendors, logging, incidents and continuity.
- Product and data explain purpose, datasets, models, changes and metrics.
- Procurement and vendor management control vendors, contracts, subprocessors and changes in terms.
- Management decides risk appetite, priorities and resources.
If the tool does not reflect these roles, the programme will end up depending on one person or parallel spreadsheets.
Where PrivaLex fits
PrivaLex does not replace the tool. It helps choose, configure and operate it with judgement. In practice, that means translating the AI Act into inventory, risk classification, controls, evidence and vendors, and connecting everything with GDPR, security, certifications and B2B customer requirements.
If the main question is which GRC platform to choose, our guide to GRC platforms for the AI Act goes into operational detail. If the question is regulatory, first review the risk logic of the EU AI Act. If personal data is involved, the programme should rely on data privacy and security.
We can help define functional requirements before buying, configure an existing platform or prepare evidence for audit, customers and management.
5 mistakes when choosing AI Act tools
Buying by brand. The best-known tool does not always fit your maturity, sector or architecture.
Not defining internal owners. Without owners, the platform accumulates tasks without real execution.
Separating AI from privacy and security. Many risks start in data, access, vendors and contracts.
Not thinking about evidence. A policy without records, tests or approvals is weak under audit.
Forgetting integration. An isolated tool can create double maintenance and more internal friction.
Final recommendation
If your company is starting, do not buy software before you have an inventory and classification criteria.
If AI already exists in product or operations, look for a tool that connects controls, evidence, vendors and reporting.
If you already have corporate GRC, assess whether it can adapt to AI before adding another layer.
And if you want to avoid an expensive mistake, define first what you need to prove. At PrivaLex, we can help prepare that map and choose the tool that actually fits. Request a free risk assessment and we will review your starting point against the EU AI Act.
Frequently asked questions
No. A tool helps operate inventories, controls, evidence and workflows, but compliance depends on correct classification, ownership and real execution of controls.
First check whether the existing GRC can extend to AI. If it supports inventory, risks, controls, evidence and vendors, adaptation may be enough. If it cannot capture models, datasets or human oversight, you need a specialist layer.
No. OneTrust fits better when AI overlaps with privacy and broad GRC; Credo AI is more focused on AI governance; Holistic AI is more oriented to assurance, assessments and technical model risks.
It makes sense if the company already works inside Microsoft and the main risk sits in data, classification, information security and compliance. By itself, it does not replace a complete AI Act programme.
An initial AI systems inventory, risk classification criteria, internal owners, involved vendors and a minimum evidence map. Without that, the purchase depends too much on vendor messaging.