These are the 9 best software tools and solutions for preparing EU AI Act compliance in Spanish companies:
- PrivaLex
- TrustWorks
- Microsoft Purview and Compliance Manager
- OneTrust AI Governance
- ServiceNow AI Control Tower
- IBM watsonx.governance
- Holistic AI
- Securiti AI Security and Governance
- Credo AI
Searching for EU AI Act software for Spanish companies is not the same as searching for a generic AI governance platform. In Spain, the buying decision is shaped by several layers at once: the EU AI Act, national supervision, GDPR, the Spanish AI sandbox guidance, the AEPD’s role when personal data is involved, and the fact that many organisations already use Copilot, ChatGPT Enterprise, AI-enabled HR tools, AI features in CRMs or internal models without a formal approval process.
The right tool depends on a prior question: which regulatory problem does the company have in Spain? An SME using internal copilots does not need the same software as a fintech using scoring, a SaaS scaleup selling AI to enterprise customers, an industrial company running predictive models in production or a group already operating ServiceNow, Microsoft 365 and corporate GRC controls. If personal data is involved, the decision should also connect with privacy risk and not treat AI as separate from GDPR implementation.
The timeline also matters. The EU AI Act, Regulation (EU) 2024/1689, entered into force on 1 August 2024. Prohibited practices and AI literacy rules have applied since 2 February 2025, and general-purpose AI model obligations since 2 August 2025. The Commission maintains an AI Act implementation platform; its page on the AI regulatory framework also reflects the simplification of certain rules, with a fixed timeline for high-risk systems: 2 December 2027 for standalone high-risk systems and 2 August 2028 for high-risk systems embedded in products. For Spanish companies, software must manage a live regulatory calendar, not a frozen checklist.
Spain also has its own institutional context. Royal Decree 729/2023 approved the AESIA statute, and Royal Decree 817/2023 regulated the Spanish AI sandbox that informed practical guidance. Software configuration should reflect that context, alongside AEPD expectations when AI relies on personal data.
The 9 best EU AI Act software tools for Spanish companies
1. PrivaLex
Before buying a platform, a Spanish company needs to turn the AI Act into its own operating model. That step is not solved by a software demo. The company must decide which AI systems are in scope, which role it plays, which obligations apply, what evidence must be retained and who can approve or block an AI use case.
At PrivaLex, we work on that layer: choosing, configuring and operating the AI compliance stack with Spanish and European requirements in mind. This includes inventory, risk classification, GDPR, DPO involvement, procurement, vendors, training, evidence, ISO 42001 and audit or due diligence readiness.
This work prevents three common buying mistakes:
- Buying a corporate GRC suite when the real issue is privacy and data.
- Buying technical model testing software when the company has not classified its systems.
- Buying an AI governance platform without knowing what evidence a customer, auditor or authority will expect.
PrivaLex is useful when the company needs to:
- Translate the AI Act into software requirements.
- Distinguish provider, deployer, importer and distributor obligations.
- Connect AI Act work with GDPR, the DPO role in AI projects, ISO 27001, NIS2 or DORA.
- Prepare a buying matrix to compare TrustWorks, OneTrust, Microsoft, ServiceNow, IBM, Holistic AI, Securiti or Credo AI.
- Configure the chosen tool so it produces real evidence, not just tasks.
For Spanish companies, the value is in connecting software with regulatory judgement. The AI Act is an EU regulation, but the interaction with AESIA, AEPD, GDPR, employment rules, public procurement and B2B customers requires a local reading.
2. TrustWorks
TrustWorks is particularly interesting for Spanish and European companies that want an AI governance platform close to privacy, compliance and cross-functional collaboration. Its AI governance page describes capabilities for discovering use cases, registering AI systems, classifying risk under the EU AI Act, managing shadow AI, assigning controls and generating documentation.
Compared with larger suites, TrustWorks sits close to day-to-day privacy and compliance work. That matters for many Spanish companies because the first AI risks often appear not in proprietary models, but in SaaS vendors, productivity tools, personal data, prompts containing sensitive information and uncontrolled employee adoption.
TrustWorks can be a good option when you need:
- AI use case records with owners, status and risk.
- Discovery of AI in external vendors and internal tools.
- Risk classification under AI Act categories.
- Controls linked to the AI Act, ISO 42001 and privacy frameworks.
- Collaboration between legal, privacy, security, product and business teams.
For a Spanish company with a reasonable GDPR programme, TrustWorks can become a practical bridge between GDPR implementation, demonstrable privacy compliance and AI governance. It does not replace legal analysis, but it can reduce manual follow-up significantly.
3. Microsoft Purview and Compliance Manager
Microsoft Purview is not a complete AI Act compliance platform on its own, but many Spanish companies should assess it because they are already deploying Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry or generative applications connected to corporate data. If the broader question is how to choose compliance tooling beyond AI, it is also worth connecting the decision with the scope of ISO 27001.
Microsoft’s official documentation on Purview protections for generative AI apps describes capabilities for managing AI usage risks, data protection and compliance controls across copilots, agents and generative AI apps. Compliance Manager also includes premium assessment templates for the EU AI Act, ISO/IEC 23894, ISO/IEC 42001 and NIST AI RMF.
Microsoft Purview can be a good option when you need:
- Visibility over prompts, responses and interactions with supported copilots or generative AI apps.
- Controls for sensitive data, labels, DLP, audit and eDiscovery.
- EU AI Act assessments inside the Microsoft environment.
- Risk management for oversharing across SharePoint, Teams, OneDrive and Microsoft 365.
- A fast starting point if Microsoft is already the company’s main platform.
The limitation is important: Purview does not classify the entire AI portfolio by itself and does not replace a dedicated AI governance platform. In Spain, it usually works best as a data and security layer within a broader AI Act, GDPR and demonstrable compliance programme.
4. OneTrust AI Governance
OneTrust AI Governance usually works best for companies with mature privacy, third-party risk, data governance or corporate GRC programmes. The official page refers to inventories of models, datasets, agents and vendors, owner assignment, risk classification with frameworks such as the EU AI Act, NIST and ISO 42001, workflows and reporting.
For large Spanish companies, OneTrust can be valuable when the AI Act does not sit alone: international vendors, GDPR records, DPIAs, procurement, contracts, internal audit, security and committee reporting all need to connect. If there is a DPO, the company should separate the DPO’s role from security, legal and business ownership.
OneTrust can be a good option when you need:
- Centralised AI, privacy and third-party risk.
- An inventory of systems, components, agents and vendors.
- Approval workflows, attestations and periodic reviews.
- Mapping across the AI Act, ISO 42001, NIST AI RMF and internal policies.
- Reporting for audit, management and enterprise customers.
The warning is the same as with any broad suite: if the process is undefined, the implementation can become heavy. Before configuring it, decide the minimum fields, escalation criteria, owners and evidence model.
5. ServiceNow AI Control Tower
ServiceNow AI Control Tower is relevant for Spanish companies already operating IT, risk, incident, security, asset or compliance processes in ServiceNow. The official page presents it as a solution to discover, govern, secure, observe and measure AI agents, models and identities. Its documentation explains a governed lifecycle from demand and intake to deployment, monitoring and closure.
This is different from a pure compliance tool. Its strength is connecting AI governance with real enterprise workflows: CMDB, asset management, incidents, exceptions, approvals, risks and value metrics.
ServiceNow can be a good option when you need:
- AI integrated into existing IT and risk operations.
- Registration of systems, models, datasets, prompts and related assets.
- Intake, approvals, risk, exceptions and incident workflows.
- Traceability of decisions inside corporate workflows.
- AI governance connected with CMDB, IT asset management and security.
For Spanish companies that already use ServiceNow, extending the current system may be more efficient than buying a separate tool. But the configuration must reflect AI Act obligations: company role, classification, transparency, human oversight, substantial changes and information to workers where applicable. If the same environment manages cybersecurity, connect it with NIS2 audit preparation to avoid duplicating evidence.
6. IBM watsonx.governance
IBM watsonx.governance is built for companies with complex environments, production models and a need for both technical governance and GRC. IBM describes watsonx.governance as an assurance, visibility and control layer for AI across hybrid and multi-vendor environments.
Its Governance Console documentation supports risk and compliance management for generative assets and machine learning models, metadata collection, workflows, quality, fairness, drift, explainability and links between use cases, business processes and regulatory mandates.
IBM can be a good option when you need:
- Governance for predictive and generative models in hybrid environments.
- AI risk connected with operational risk, third parties, continuity and IT.
- Monitoring for quality, drift, fairness and explainability.
- Factsheets and model documentation throughout the lifecycle.
- AI governance in a large or regulated organisation.
In Spain, it can be especially relevant for banking, insurance, industry, healthcare, energy or groups with complex architecture. In fintech, for example, AI governance may overlap with DORA; in energy, with NIS2; and in healthcare, with connected-device security. It is usually not the lightest option for an SME starting with inventory and training.
7. Holistic AI
Holistic AI stands out for technical assessment, testing, assurance and continuous governance. Its platform focuses on detecting AI, protecting systems and enforcing controls throughout the lifecycle, with tests for bias, fairness, robustness, security, toxicity, hallucination, prompt injection and audit-ready evidence.
This matters for Spanish companies that do not merely use AI tools, but deploy systems that affect people: recruitment, scoring, pricing, healthcare, education, sensitive customer service, fraud or access to services.
Holistic AI can be a good option when you need:
- Technical testing over models and agents, not only compliance questionnaires.
- Evidence on bias, robustness, security, explainability or performance.
- Red teaming or assessment of generative systems.
- Controls for high-impact use cases.
- AI Act, ISO 42001 and NIST AI RMF readiness with an assurance lens.
The key is not to use it as a substitute for internal governance. Technical tests are powerful, but they need to connect with business decisions, human oversight, documentation, contracts and accountability.
8. Securiti AI Security and Governance
Securiti can be useful when the company’s core issue is the relationship between data and AI. Its AI Security and Governance solution is designed to discover and catalogue models across public clouds, private clouds and SaaS applications, map data to AI, assess risks, apply controls and automate compliance.
It is worth considering when AI Act exposure overlaps with personal, confidential or regulated information: customer data, employee data, patient data, insured persons, financial users or sensitive industrial data.
Securiti can be a good option when you need:
- Discovery of AI models and systems in cloud, SaaS and internal projects.
- Mapping of which data feeds each system.
- Controls over personal or confidential data exposure.
- Connection between AI governance, privacy, data intelligence and security.
- Visibility across multi-cloud environments.
For Spanish companies with heavy GDPR exposure, Securiti can be valuable if it integrates with records of processing, DPIAs, vendor management and security controls. This layer is easier to design after a privacy maturity review.
9. Credo AI
Credo AI is a specialist AI governance platform focused on registry, risk intelligence, policy engine, evidence recording and agent governance. Its official site describes capabilities to discover systems, agents, models and vendors, classify risk, map controls and generate evidence for frameworks such as the EU AI Act, ISO 42001 and NIST AI RMF.
It can be particularly useful for organisations where AI programmes are distributed across product, data, engineering, legal, compliance and security teams, and where one common place is needed to govern applications, models, agents and vendors.
Credo AI can be a good option when you need:
- A dedicated registry for systems, agents, models and vendors.
- Policy packs for the EU AI Act, ISO 42001 and other frameworks.
- Controls for agentic AI and autonomous systems.
- Integrations with engineering and collaboration tools.
- Continuous evidence beyond a point-in-time review.
For Spanish companies, its strongest value appears when there is in-house AI development or accelerated AI adoption across several business units. If the company only needs to organise copilots and SaaS tools, it may be more platform than needed in phase one.
What AI Act software should cover in Spain
A strong tool for Spanish companies should not stop at “AI Act compliance” as a commercial label. It should cover these blocks in a verifiable way:
- Inventory and scope. Proprietary systems, AI-enabled SaaS, copilots, agents, APIs, models, datasets and vendors.
- Company role. Provider, deployer, distributor, importer, integrator or internal user with concrete obligations.
- Risk classification. Prohibited, high-risk, transparency-related, limited-risk or minimal-risk, with justification and review date.
- Obligations by category. Different controls for prohibited systems, high-risk systems, transparency duties, GPAI or internal use.
- GDPR and AEPD. DPIAs, legal basis, information notices, automated decisions, minimisation, accuracy and rights. For systems involving personal data, AEPD guidance on GDPR compliance for AI-based processing remains a useful reference.
- Evidence. Approvals, tests, instructions for use, logs, human reviews, training, contracts and incidents.
- Human oversight. People with competence, authority and support, not just a checkbox.
- Training and AI literacy. Training records by role, system and risk, connected with how to prove staff training in an audit.
- Vendors. Contracts, subprocessors, location, instructions, technical documentation and changes in terms.
- Reporting. Packages for management, enterprise customers, internal audit, AESIA, AEPD or due diligence.
The AESIA guidance, developed from the Spanish AI sandbox, is especially useful for translating these blocks into concrete requirements: conformity assessment, quality management system, risk management, human oversight, data and data governance, transparency, accuracy, robustness, cybersecurity, records, post-market monitoring, incidents and technical documentation.
How to decide by company type
Not every company needs the same stack.
SME using third-party AI. It usually needs an inventory, generative AI use policy, sensitive data controls, training, vendor review and basic evidence. Microsoft Purview, TrustWorks or a lighter setup supported by PrivaLex may be enough. If documentation is weak, start by organising privacy policies and vendor records.
SaaS scaleup selling to enterprise customers. It needs to answer questionnaires, demonstrate controls, document AI in the product, manage vendors, prepare commercial evidence and connect the AI Act with regulatory compliance automation. TrustWorks, OneTrust, Credo AI or Holistic AI may enter depending on technical maturity.
Company using AI in HR or decisions about people. It should pay close attention to Annex III, GDPR, transparency, information to workers, human oversight, bias and employment law. Holistic AI, Credo AI, OneTrust or ServiceNow may help, but legal and privacy analysis should come first.
Group using Microsoft 365 and Copilot. Purview and Compliance Manager are almost unavoidable as the data, prompt, audit and template layer. But they should be complemented with AI governance tooling if systems exist outside Microsoft.
Regulated company or production-model environment. Banking, insurance, healthcare, energy, industry or critical infrastructure need more depth: model risk, drift, fairness, cybersecurity, logging, vendors, continuity and audit. IBM, Holistic AI, ServiceNow, Securiti or OneTrust may make sense depending on architecture.
Spanish provider of AI systems. If the company sells AI systems, especially in sensitive areas, it needs requirements management, technical documentation, QMS, conformity assessment, post-market monitoring, incidents and substantial change management. The software must cover more than inventory and should align with how the AI Act and ISO 42001 work together.
9 mistakes when choosing EU AI Act software
Buying before classification. If you do not know whether you are a provider or deployer, or which systems are high-risk, the platform will be configured blindly.
Using old timelines. Many pages still refer to August 2026 as if every obligation applied in the same way. Check the current official timeline and Commission updates.
Forgetting AESIA and AEPD. In Spain, AI supervision and data protection overlap. An AI system involving personal data can trigger obligations under both the AI Act and GDPR.
Confusing Copilot with full compliance. Microsoft may cover an important part of data and security, but not the whole legal classification or the full AI governance programme.
Ignoring shadow AI. If employees use generative tools outside the formal process, the company still has operational and data risk.
Not retaining evidence. The tool must preserve why a system was approved, who reviewed it, which tests were performed and when it must be reviewed again.
Separating AI from procurement. Many risks arrive through SaaS vendors with AI features enabled without contract review.
Treating training as generic awareness. AI literacy should reflect the role, system and risk. It can connect with a corporate training plan, but it needs AI-specific content.
Failing to prepare the customer evidence package. In B2B, software should help answer due diligence: inventory, controls, vendors, training, incidents, privacy and security.
Final recommendation
If your Spanish company is starting now, do not buy AI Act software by brand alone. Start with serious classification of systems, roles, data, vendors and evidence.
If you already use Microsoft, review Purview and Compliance Manager as your data and security layer. If you already have GRC, assess whether it can be adapted with AI-specific fields. If you have proprietary models or high-impact systems, look for a platform with technical testing, lifecycle governance and robust evidence.
And if you need to decide without losing months in demos, PrivaLex can help define requirements, compare options and configure the software around what a Spanish company actually needs to prove: AI Act compliance, GDPR, training, vendors, security, audit and commercial trust.
Request a free risk assessment and we will review which software and operating model your company needs before investing.
Frequently asked questions
It depends on the AI use case. At minimum, the software should cover inventory, risk classification, vendors, evidence, training, privacy and reporting. For high-risk systems or proprietary models, deeper technical controls, documentation and monitoring will be needed.
Not by itself. Purview can be very useful for data, Copilot, prompts, DLP, audit and Compliance Manager, but the company still needs system classification, role analysis, vendor governance, human oversight, evidence and AI Act-specific obligations.
It should check which AI systems it uses, whether it is a provider or deployer, which personal data is involved, which vendors participate, whether decisions affect people and what evidence will be needed for customers, AESIA, AEPD or audit.
It should allow the company to record training, roles and AI literacy evidence. Article 4 of the AI Act requires providers and deployers to ensure a sufficient level of AI literacy, considering context and the people dealing with AI systems.
The company should look for a tool that covers high-risk classification, bias, human oversight, information to workers or candidates, DPIAs where relevant, review evidence and vendor control. Holistic AI, Credo AI, OneTrust or ServiceNow may help depending on maturity.
No. What matters is that the company can demonstrate classification, controls, documentation, evidence, risk management, oversight, records and incidents. AESIA guidance helps structure these requirements, but it does not impose a software brand.