What's the best EU AI Act compliance software?

No product is best for every buyer. The software splits into four categories (GRC automation, enterprise AI governance, LLM observability and runtime control planes), and many regulated teams run two: a governance system of record, and a way to control and record what their highest-risk AI does in production. Score candidates with the evaluation worksheet on this page.

How do I choose compliance software for dual GDPR and EU AI Act readiness?

Start from your roles: controller or processor under the GDPR, provider or deployer under the AI Act. List the duties both laws give you: impact assessments (DPIA and FRIA), human review of automated decisions (GDPR Article 22, AI Act Article 14), records (GDPR Article 30, AI Act Articles 12 and 26(6)) and notices. Then ask each vendor to show one record that serves both regulators, and check its data-processing terms under GDPR Article 28.

Where can I buy compliance software for dual GDPR and EU AI Act readiness?

Buy directly from the vendor. Observability tools such as Langfuse, LangSmith and Arize publish self-serve price lists. GRC, enterprise AI governance and runtime control platforms sell through a scoped quote. Before signing, ask for an EU hosting region, a GDPR Article 28 data processing agreement, the sub-processor list and an export of your records on exit.

What is the cost of compliance software for GDPR and the EU AI Act?

Published October 2026 prices: Langfuse cloud from free to USD 2,499 a month and free to self-host; LangSmith Plus USD 39 per seat a month; Arize AX Pro USD 50 a month. KLA starts with a four-week SAFR Production Sprint from EUR 5,000. GRC and AI governance platforms quote per contract, so ask which unit they price by (seats, frameworks, AI systems or agents) and what year two costs.

What's the best EU AI Act compliance software for enterprises?

Enterprises with large AI portfolios usually start with an enterprise AI governance platform (OneTrust, Credo AI, Holistic AI, IBM watsonx.governance) as the system of record for discovery, classification and impact assessments. They add runtime control for the high-risk workflows where they must show human oversight (Article 14) and records an auditor can use (Article 12).

What's the best EU AI Act compliance software for startups?

If AI is one framework among SOC 2, ISO 27001 and GDPR, a GRC platform (Vanta, Drata, Secureframe) covers the most ground for one contract. If you ship a high-risk or agentic product, give priority to runtime control that records oversight on the decisions that carry regulatory exposure.

When does the EU AI Act high-risk deadline fall?

Regulation (EU) 2026/1744, the Digital Omnibus on AI, was published in the Official Journal on 24 July 2026 and has been in force since 27 July 2026. It moved stand-alone Annex III high-risk obligations, the Article 27 FRIA and Article 49 registration to 2 December 2027, and high-risk AI in Annex I products to 2 August 2028. Article 50 transparency duties have applied since 2 August 2026, and the grace period for marking AI-generated content ends on 2 December 2026.

Does KLA have a commercial interest in this guide?

Yes. KLA publishes this guide and sells KLA Control Plane, a runtime control plane. The other vendors are described from their own public pages as checked in October 2026. The guide does not rank vendors.

What type of software proves an AI agent action was governed?

A runtime control plane can show the policy verdict, approval or escalation, executed tool call, business outcome, and integrity evidence for one action. Portfolio governance software supplies the surrounding inventory and assessment records.

Do regulated teams need both GRC and runtime AI governance software?

Many regulated teams use a governance or GRC system for portfolio breadth and a runtime layer for consequential actions. The right combination follows the system boundary, risk classification, and evidence responsibility.

How do I choose EU AI Act software for high-risk agent workflows?

Map the product to the job it owns: inventory and assessment, engineering observability, or decision-time control. Ask vendors to demonstrate a complete action record with policy, human decision, downstream effect, retention, and independent verification.

Where does a compliance software selector fit in the buying process?

A selector helps identify the software category that matches the immediate operating gap. Validate the result against intended purpose, role, affected people, current evidence, and the controls required in production.

Buyer's guide

Best EU AI Act compliance software 2026: A buyer's guide

Updated October 2026. EU AI Act compliance software splits into four categories: GRC automation, enterprise AI governance, LLM observability, and runtime control planes. How to choose, where to buy and what it costs for GDPR and AI Act work, with vendor claims checked in October 2026 and an evaluation worksheet.

Short answer

Choose by the job you need done. GRC automation (Vanta, Drata, Secureframe) runs GDPR and AI Act work in one programme. Enterprise AI governance (OneTrust, Credo AI, Holistic AI, IBM watsonx.governance) keeps the AI inventory and assessments. LLM observability serves engineers. A runtime control plane holds high-risk actions for approval and records evidence. KLA, the publisher, sells the last category.

For enterprises

Use an enterprise AI governance platform as the system of record for inventory, classification and impact assessments. Add runtime control where an agent takes high-risk actions and you must show who approved each one.

For startups

If AI is one framework next to SOC 2, ISO 27001 and GDPR, a GRC platform is the simplest start. If your product is a high-risk or agentic system, test runtime control early, because Article 12 records and Article 14 oversight are hard to add later.

For dual GDPR + AI Act

Keep one system description behind the GDPR DPIA (Article 35) and the AI Act FRIA (Article 27), and one record of each human review. Article 27(4) lets the FRIA complement an existing DPIA. See the dual GDPR and AI Act section.

Disclosure: KLA publishes this guide and sells KLA Control Plane, which sits in the runtime control plane category. We describe other vendors from their own public product and pricing pages, checked in October 2026, and we link each source. The guide groups products by the job they do and does not rank them.

"AI compliance software" covers four kinds of product: GRC automation, enterprise AI governance, LLM and agent observability, and runtime control planes. The lines between them moved in 2026. Drata and Vanta now announce agent-governance products, and OneTrust and Holistic AI describe blocking or escalating agent actions at runtime. Use the categories to decide which job you are buying for, then test each vendor against that job.

The deadlines are now law. The Digital Omnibus on AI was published in the Official Journal as Regulation (EU) 2026/1744 on 24 July 2026 and has been in force since 27 July 2026. Stand-alone high-risk systems (Annex III) must comply from 2 December 2027, and high-risk AI in regulated products (Annex I) from 2 August 2028. Article 50 transparency duties have applied since 2 August 2026; the grace period for marking AI-generated content ends on 2 December 2026.

The first harmonised standard is also in place. On 14 October 2026 the Commission cited EN 18286:2026, the quality management system standard, in the Official Journal (Implementing Decision (EU) 2026/2274). Providers that follow it get a presumption of conformity for the Article 17 requirements it covers. See what the citation changes for Article 17 and the EN 18286 explainer.

Bottom line

Name your system of record first: an enterprise AI governance platform, or a GRC platform if AI sits inside a wider programme. Then decide whether your highest-risk workflows also need runtime control that holds an action for approval and records the decision. For GDPR and AI Act work together, choose tools that keep one system description and one review record for both regulators.

Last updated: October 20, 2026 · Version v3.0 · Not legal advice.

Open compare pages Evidence pack checklist

Scope, evidence, and sources

Reference notes

Scope, evidence, and sources

Definition

EU AI Act compliance software covers distinct layers of work: program management, AI-system inventory and assessment, engineering observability, and runtime control. A suitable stack depends on whether a team needs portfolio governance, developer telemetry, or enforceable decisions and evidence for high-risk AI actions. The comparison belongs to the buyer's operating scope and the system's intended purpose.

Scope and exceptions

Applies when: Use this framework when comparing software for AI governance, EU AI Act readiness, or production control of agentic workflows. Start with system-of-record, risk-classification, and runtime-action questions.
Exceptions: Template-only work, legal interpretation, and sector-specific conformity assessment require the responsible legal, compliance, or notified-body process.

Decision framework

GRC automation: multi-framework program breadth and evidence coordination.
Enterprise AI governance: AI inventory, classification, and impact assessments.
LLM and agent observability: engineering traces, evaluation, and debugging.
Runtime control plane: policy, human oversight, and case-level execution evidence.

Minimum evidence

Intended purpose, operator role, affected people, and applicable risk classification.
Control owner, policy version, decision outcome, and approval or escalation record.
Agent, model, tool, data boundary, and business-action identifiers for each governed case.
Evidence export manifest, hashes or signatures, retention rule, and verification method.

Worked regulated workflow

Loan-onboarding software stack selection

Scenario: A bank uses an agent to assemble an application, call a credit-risk model, and route borderline cases to an underwriter.

Workflow: The governance system records the AI inventory, intended purpose, classification, and impact assessment. A runtime control plane evaluates the proposed decision, creates a Decision Request for the underwriter, and links the approval, outcome, and sealed evidence to the case. The buyer can then assess portfolio coverage and action-level proof as separate responsibilities.

Questions buyers ask

What type of software proves an AI agent action was governed?: A runtime control plane can show the policy verdict, approval or escalation, executed tool call, business outcome, and integrity evidence for one action. Portfolio governance software supplies the surrounding inventory and assessment records.
Do regulated teams need both GRC and runtime AI governance software?: Many regulated teams use a governance or GRC system for portfolio breadth and a runtime layer for consequential actions. The right combination follows the system boundary, risk classification, and evidence responsibility.
How do I choose EU AI Act software for high-risk agent workflows?: Map the product to the job it owns: inventory and assessment, engineering observability, or decision-time control. Ask vendors to demonstrate a complete action record with policy, human decision, downstream effect, retention, and independent verification.
Where does a compliance software selector fit in the buying process?: A selector helps identify the software category that matches the immediate operating gap. Validate the result against intended purpose, role, affected people, current evidence, and the controls required in production.

Primary sources

Reviewed: October 20, 2026

How KLA Control Plane implements this

KLA Control Plane occupies the runtime control layer for agent actions. It intercepts proposed actions, applies policy and approval decisions, and produces execution evidence that connects the control to the business outcome.

Capability: Explore the capability
Technical reference: Read the technical reference
Practical artifact: EU AI Act software selector

Scope boundary: Portfolio inventory, legal interpretation, and multi-framework program management remain with the buyer's governance and compliance systems. KLA addresses the execution layer.

Verdict

The 30-second answer

The four categories at a glance (vendor claims checked October 2026)
Category	Primary job	Examples	Strongest EU AI Act fit	What to test	Choose it when
GRC automation	Run AI compliance inside a multi-framework programme that already covers GDPR	Vanta, Drata, Secureframe	Programme management, inventories, cross-framework evidence (SOC 2, ISO 27001, ISO 42001, GDPR, AI Act)	Agent-governance features are new: Vanta lists a waitlist and Drata limited availability	AI is one risk domain among many and you want one home for all of them
Enterprise AI governance	An AI system of record: discovery, classification, impact assessments	OneTrust, Credo AI, Holistic AI, IBM watsonx.governance	Articles 9 and 11, impact assessments, cross-functional governance	Which runtimes the enforcement features support, and how a human approval is recorded	You need structured governance across a large portfolio of AI systems
LLM / agent observability	Trace, evaluate and monitor LLM apps	LangSmith, Langfuse, Arize AI	Engineering logs that support Article 12 and Article 15 testing	Retention periods, export format, and who can change a trace	Engineering needs to debug and evaluate models and agents
Runtime control plane	Evaluate each high-stakes agent action before it runs, hold it for human approval, and record verifiable evidence	KLA (publisher of this guide)	Article 14 oversight, Article 12 records with integrity checks, Annex IV evidence for governed workflows	Supported agent frameworks and integration routes	Agents take high-risk actions and you must show an auditor who approved what

Dual GDPR and AI Act compliance: how to choose, where to buy, what it costs

The GDPR and the AI Act ask for overlapping records. An AI system that uses personal data to make or support decisions about people often needs a GDPR data protection impact assessment (DPIA, Article 35). If the system is high-risk, the deployer may also need an AI Act fundamental rights impact assessment (FRIA, Article 27) from 2 December 2027. Article 26(9) tells deployers to use the provider's Article 13 instructions for their DPIA, and Article 27(4) lets the FRIA complement a DPIA that already covers some of its points. Software for both laws should keep one system description and one evidence trail behind both assessments.

How to choose. (1) Write down your roles: controller or processor under the GDPR, provider or deployer under the AI Act. (2) List the duties in the table below that apply to you. (3) Ask each vendor to show one record that serves a data protection authority and a market surveillance authority, for example a reviewed automated decision with the reviewer, the information shown and the outcome. (4) Score the answers with the evaluation worksheet.

Where to buy. All vendors in this guide sell directly. Langfuse, LangSmith and Arize publish self-serve plans; GRC, enterprise AI governance and runtime control platforms quote per contract. Before you sign, ask for an EU hosting region, a GDPR Article 28 data processing agreement, the sub-processor list, the international transfer mechanism, and a full export of your records if you leave.

What it costs. Published prices in October 2026: Langfuse cloud Hobby free, Core USD 29, Pro USD 199 and Enterprise USD 2,499 a month, and free to self-host; LangSmith Developer free and Plus USD 39 per seat a month; Arize AX Free and AX Pro USD 50 a month. KLA's SAFR Production Sprint starts at EUR 5,000 for four weeks, and Production is priced per governed AI application, model or Process. Usage above the included volume is billed separately. For quoted platforms, ask for the pricing unit, the year-two price and the cost of exit exports.

GDPR changes are still a proposal. The Commission's Digital Omnibus proposal of 19 November 2025 (COM(2025) 837) would amend parts of the GDPR. In October 2026 it was awaiting a committee decision in the European Parliament (procedure 2025/0360(COD)), so buy against the GDPR as it stands. The free DPIA and FRIA generator runs both assessments in one pass with a shared risk register.

Where GDPR and AI Act duties meet, and what the software should hold
Duty	GDPR	EU AI Act	What the software should hold
Impact assessment	DPIA for high-risk processing (Art. 35)	FRIA for certain deployers of Annex III systems from 2 Dec 2027 (Art. 27); the FRIA complements an existing DPIA (Art. 27(4))	One system description, risk list and owner list shared by both assessments
Decisions about people	Rights on solely automated decisions with legal or similar effects, including human intervention (Art. 22)	Human oversight for high-risk systems (Art. 14); deployers assign competent overseers (Art. 26(2))	Each reviewed case: reviewer, information shown, decision, time
Records	Records of processing activities (Art. 30)	Automatic logs (Art. 12); deployers keep logs for at least six months (Art. 26(6))	A processing register plus per-run logs with a retention rule
Information to people	Notices to data subjects (Arts. 13–14)	Article 50 transparency since 2 Aug 2026; deployers of Annex III systems inform the people affected (Art. 26(11))	Notice versions and the dates each was shown
Provider information	Controller relies on processor terms (Art. 28)	Deployers use the provider's instructions for use (Art. 13) for their DPIA (Art. 26(9))	Provider documentation stored with the DPIA and FRIA

What each vendor says it does (checked October 2026)

Each row summarises the vendor's own public page. Vendor pages change often and describe features in the vendor's words; confirm availability and scope in a demo. KLA is the publisher of this guide.

In one buyer conversation, a professional-services firm that builds many agents in a hosted low-code agent builder asked us for approvals and tool-use controls over agents that run in another vendor's cloud. The design question was where the control point sits. Inline control needs each tool call to pass through the control point before it runs. Reading the agent platform's audit log afterwards gives detection only. Ask each vendor which of the two it offers for your agent platform.

Vendor	Category	What the vendor's page describes	Availability noted	Source
Vanta	GRC automation	ISO 42001 templates and mapped controls reusable for the EU AI Act. An AI governance product that maps agents, models, prompts and data, attests EU AI Act use cases, and alerts on activity outside approved boundaries.	AI governance: waitlist	AI governance, ISO 42001
Drata	GRC automation	ISO 42001 framework. AI Agent Governance discovers agents, checks commands and tool calls against policy, blocks violations before they run, and logs each decision in a tamper-evident record mapped to ISO 42001, the EU AI Act and AIUC-1.	Agent governance: limited availability	Agent governance, ISO 42001
Secureframe	GRC automation	Supported frameworks include ISO 42001, NIST AI RMF and the EU AI Act, with control mapping, automated tests and cross-framework evidence.	Not stated	Framework offering
OneTrust	Enterprise AI governance	Inventory of AI systems, agents, models, datasets and vendors. EU AI Act, NIST AI RMF and ISO 42001 templates. Runtime monitoring for Amazon Bedrock and Microsoft Foundry. Guardrail enforcement that can block, allow, redact, escalate or route.	Not stated	AI governance
Credo AI	Enterprise AI governance	AI Registry for systems, agents, vendors and models. Policy packs for the EU AI Act, NIST AI RMF and ISO 42001. Monitoring through connected observability tools.	Agent Governor: research preview	credo.ai
Holistic AI	Enterprise AI governance	Discovery and inventory. Controls mapped to the EU AI Act, NIST AI RMF and ISO/IEC 42001. Testing for bias, hallucination and prompt injection. Agents that block or pause non-compliant agent actions.	Not stated	holisticai.com
IBM watsonx.governance	Enterprise AI governance	Lifecycle governance, risk management, shadow-AI detection and policy enforcement. Lists the EU AI Act among supported frameworks.	14-day trial	watsonx.governance
LangSmith	Observability	Tracing and evaluation for LLM apps and agents. Cloud in the US or EU, hybrid, or self-hosted on Enterprise.	Developer free; Plus USD 39 per seat a month	Pricing
Langfuse	Observability	Open-source tracing and evaluation. Cloud regions in the US, EU and Japan.	Free to self-host; cloud from free to USD 2,499 a month	Pricing
Arize AI	Observability	Phoenix (open source) and Arize AX: tracing, evaluations, monitors and human annotation queues.	AX Free; AX Pro USD 50 a month	Pricing
KLA (publisher)	Runtime control plane	Evaluates each proposed agent action as allow, warn, require_approval or block; routes approvals to Decision Desk; exports a Sealed Evidence Bundle with an independent verification run.	SAFR Production Sprint from EUR 5,000	Pricing

Decision tree

Which layer do you actually need?

Match the symptom to the category before you compare features.

“We manage SOC 2, ISO 27001 and GDPR, and AI is the next framework.”

GRC automation platform

“We have dozens of AI systems and no single place to inventory, classify and assess them.”

Enterprise AI governance platform

“Our engineers need to debug prompts, latency and model behaviour.”

LLM / agent observability

“We are letting an agent take actions that need a human in the loop, and we will have to prove that to a regulator.”

Runtime control plane

“More than one of the above is true.”

A small stack: a system of record for breadth, plus a runtime layer for the high-risk decisions

Requirements

What the EU AI Act actually requires

Risk management system (Article 9): Ongoing identification and mitigation of risks.

Risk management system (Article 9): Ongoing identification and mitigation of risks.
Data governance (Article 10): Quality standards for training and validation data.
Technical documentation (Article 11 + Annex IV): Comprehensive documentation of the AI system.
Record-keeping (Article 12): Automatic logging of system operations.
Transparency (Article 13): Clear information for deployers.
Human oversight (Article 14): Mechanisms for human monitoring and intervention.
Accuracy, robustness, cybersecurity (Article 15): Performance and security standards.
Quality management system (Article 17): A documented QMS for providers; EN 18286:2026 is the cited harmonised standard.
Post-market monitoring (Article 72): Ongoing surveillance after deployment.

Market map

Tool categories that buyers actually compare

GRC automation platforms

Examples: Vanta, Drata, Secureframe

Strengths

Multi-framework compliance management across SOC 2, ISO 27001, ISO 42001, GDPR and EU AI Act work.
Continuous evidence collection from cloud infrastructure, identity systems, HR systems and engineering tooling.
Control libraries, task management and audit workflows that fit existing security and compliance teams.
Trust centres, questionnaires and customer assurance operations.
Agent governance is arriving in this category: Drata describes blocking agent actions that break policy, and Vanta describes alerts on agent activity outside approved boundaries.

Limitations

The agent-governance products were in limited availability (Drata) or on a waitlist (Vanta) in October 2026.
Evidence is often strongest for surrounding systems and controls; check the record for a single governed AI decision.
Ask how a human approval of a specific business action is captured and exported.

Best for: Organisations managing several compliance frameworks, including GDPR, that want AI compliance inside an existing GRC operating model.

EU AI Act coverage: Strongest on programme management, inventories, evidence collection and cross-framework reporting. Depth on workflow-level human oversight and case-level execution evidence varies by vendor and by product availability.

Enterprise AI governance platforms

Examples: OneTrust, Credo AI, Holistic AI, IBM watsonx.governance

Strengths

AI discovery, inventory and lifecycle documentation for large portfolios of systems, agents, models and vendors.
Impact assessments and policy packs for the EU AI Act, NIST AI RMF and ISO 42001.
Cross-functional coordination across legal, privacy, security, procurement and business owners.
Runtime features are growing: OneTrust describes guardrail enforcement that can block, redact, escalate or route; Holistic AI describes agents that block or pause non-compliant actions.

Limitations

Runtime enforcement covers specific platforms; OneTrust names Amazon Bedrock and Microsoft Foundry for runtime monitoring. Check support for your agent stack.
Credo AI lists its Agent Governor as a research preview.
Ask how a named reviewer approves one business action and how that approval appears in the export.
Implementation can be heavier because these platforms aim to standardise governance across the enterprise.

Best for: Enterprises that need structured AI governance across many systems, with a clear operating model for discovery, documentation, policy and ongoing oversight.

EU AI Act coverage: Often strong on Articles 9 and 11, impact assessments and governance coordination. Coverage of Articles 12 and 14 depends on how close the product sits to the runtime decision path.

LLM observability platforms

Examples: LangSmith, Langfuse, Arize AI

Strengths

Tracing and debugging LLM applications and agents.
Evaluation runs, datasets and prompt versioning.
Latency, token and cost tracking.
Human annotation queues for reviewing outputs (Arize).
Published self-serve prices and open-source options (Langfuse, Phoenix).

Limitations

Built for engineering teams; the records are traces and evaluations.
Approval of a business action before it runs is outside the products as described on their pages.
Default trace retention is short on lower plans (14 days for LangSmith base traces, 15 days on Arize AX Free); check it against your retention duty.

Best for: Engineering teams building, testing and debugging LLM applications and agents.

EU AI Act coverage: Supports Article 12 logging and Article 15 testing work. Governance, oversight and assessment duties need another layer.

Runtime control planes

Examples: KLA (publisher of this guide)

Strengths

Decision-time policy evaluation with four outcomes: allow, warn, require_approval and block.
Human approval in Decision Desk, with escalation and the reviewer's decision recorded.
Evidence captured from each governed execution.
Sealed Evidence Bundles that an outside reviewer can verify.

Limitations

KLA is a runtime layer; it does not run a multi-framework GRC programme or an enterprise-wide AI inventory.
It does not provide development-time observability, model training or experimentation.
It needs integration into the agent execution path.

Best for: Organisations whose AI agents take high-risk actions that need human approval and records an auditor can check.

EU AI Act coverage: Article 14 human oversight, Article 12 record-keeping with integrity checks, and Annex IV evidence for governed workflows.

Coverage map

Which obligation does each layer cover?

Core high-risk obligations mapped to the layer that primarily helps
Obligation	What it requires	Layer that primarily helps
Risk management (Art. 9)	Ongoing identification and mitigation of risks	Governance platform
Data governance (Art. 10)	Quality standards for training and validation data	Governance platform
Technical documentation (Art. 11 + Annex IV)	Comprehensive system documentation	Governance platform + runtime evidence
Record-keeping (Art. 12)	Automatic logging of system operations	Runtime control plane (audit records) / observability (developer logs)
Transparency to deployers (Art. 13)	Clear information for deployers	Governance platform
Human oversight (Art. 14)	Mechanisms for human monitoring and intervention	Runtime control plane
Accuracy, robustness, cybersecurity (Art. 15)	Performance and security standards	Observability + governance platform
Quality management system (Art. 17)	A documented QMS for providers; EN 18286:2026 gives a presumption of conformity for the parts it covers	GRC / governance platform
Post-market monitoring (Art. 72)	Ongoing surveillance after deployment	Runtime control plane + governance platform
Incident reporting (Art. 73)	Reporting of serious incidents	Governance platform + runtime evidence

Shortlist

How to evaluate vendors

Role and scope

Be clear whether you are buying for a provider, a deployer, or both, and whether this tool is your system of record or a specialised layer.

Look for

Clarity on provider and deployer responsibilities, and on controller and processor roles under the GDPR.
Support for your governance operating model across legal, compliance and engineering teams.
A realistic answer to whether this tool is your primary system of record or a specialised layer.
A clear view of where another tool is expected to complement it in a high-risk stack.

Ask

Which EU AI Act obligations do you support for providers, deployers, or both?
Are you the system of record, the runtime control layer, or a complement to another platform?
Where do you expect another tool to complement you in a high-risk stack?

Runtime depth

Many vendors now describe "runtime governance". Find out whether that means monitoring and alerts, guardrails on model inputs and outputs, or authority to stop a business action before it runs.

Look for

Policy evaluation at execution time.
Ability to halt, reroute or require approval before the action completes.
Integration into the decision path, alongside any downstream monitoring feed.
A clear distinction between monitoring, downstream review and inline approval.

Ask

What happens in the product when a high-risk action must be blocked pending review?
Do you support named approvers, escalation paths and override capture for business actions?
Which controls are inline, and which are post-hoc monitoring or review?
Is this feature generally available, in preview, or on a waitlist?

Evidence and audit readiness

Auditors work from evidence records. Check what one record contains.

Look for

Evidence tied to a specific AI execution.
Clear mapping to Annex IV documentation requirements.
Structured formats auditors can work with.
Completeness of the evidence package.

Ask

Can you show me a sample evidence export tied to a single execution?
How does it map to Annex IV requirements?
What format does an auditor actually receive?

Independent verifiability

Check whether an auditor can confirm the evidence is unchanged without relying on the vendor.

Look for

Cryptographic integrity verification.
Tamper-evident storage.
Independent verification mechanisms.
Chain-of-custody documentation.

Ask

How can an auditor verify the evidence hasn't been modified?
Is storage tamper-evident, with chain-of-custody documentation?
Can verification happen without logging into your platform?

Operations after go-live

Check how the product behaves once it is live: under SLA pressure, policy change and multi-year retention.

Look for

Approval workflows that degrade gracefully when a reviewer misses an SLA.
A defined process for post-market monitoring, incidents and policy changes.
Multi-year evidence retention and export.
Documentation of oversight actions and overrides.

Ask

How do approval workflows behave when a reviewer misses an SLA?
How do you handle post-market monitoring, incidents and policy changes?
What does evidence retention look like over several years?

GDPR and data location

Personal data passes through every one of these tools. Check the processing terms before the features.

Look for

A GDPR Article 28 data processing agreement and a current sub-processor list.
An EU hosting region or a self-hosted option.
Retention settings you control, and deletion on request.
A full export of your records when the contract ends.

Ask

Where is our data stored and processed, and under which transfer mechanism?
Can we set retention per record type to match GDPR and AI Act duties?
What do we receive, in which format, when we leave?

Evaluation worksheet

Copy this table into a spreadsheet, add one column per vendor, and fill it from demos and documents. Record the source and the date you checked it, because vendor pages and availability change. Score each row 0 (not shown), 1 (described in documents) or 2 (shown working on your data).

Criterion	Evidence to request	Source and date checked	Score (0–2)
Role fit	Which AI Act roles (provider, deployer) and GDPR roles (controller, processor) the product supports
DPIA and FRIA	Both assessments built from one system description (GDPR Art. 35, AI Act Art. 27)
Human oversight	One recorded approval of a consequential action: reviewer, information shown, decision, time
Runtime control	A live demo of an action held or blocked before it runs, and what the agent receives back
Records and retention	Log schema, retention setting and an export of one run (AI Act Arts. 12, 19, 26(6))
Evidence integrity	How an outside reviewer checks that an export was not altered, without logging in to the product
Standards mapping	For providers: QMS templates mapped to EN 18286:2026 clauses
Data protection terms	GDPR Art. 28 agreement, sub-processor list, EU hosting region, transfer mechanism
Cost	Pricing unit, year-one and year-two price, overage rates, exit export
Availability	Whether each feature you score is generally available, in preview or on a waitlist

Use cases

Recommendations by use case

Broad GRC and trust-programme operations

Shortlist: Vanta, Drata, Secureframe

Strengths

Multi-framework efficiency, including GDPR
Strong surrounding-system evidence collection
Trust-centre and questionnaire workflows

Gaps

Vanta and Drata agent-governance products were on a waitlist or in limited availability in October 2026
Evidence is often stronger at the programme and system layer than at the single-decision layer

Enterprise AI governance system of record

Shortlist: OneTrust, Credo AI, Holistic AI, IBM watsonx.governance

Strengths

AI-specific governance operating model
Discovery, policy and assessment workflows
Cross-functional enterprise coordination

Gaps

Runtime enforcement support varies by agent platform
Case-level approval records and exports need a demo on your workflow

Developer observability for LLMs and agents

Shortlist: LangSmith, Langfuse, Arize AI

Strengths

Developer experience
Debugging and evaluation
Published prices

Gaps

Built for engineering records
No business-action approval workflow

Workflow-level decision governance and audit evidence

KLA (publisher of this guide)

Strengths

Decision-time controls
Approval queues with accountability
Portable, verifiable evidence exports

Gaps

AI-focused rather than multi-framework
Requires integration into AI execution path

Need both enterprise governance breadth and runtime records

A governance or GRC platform plus a runtime control plane

Strengths

Governance system of record plus workflow-level evidence
Closer alignment between policy, oversight and production execution
One review record for both GDPR and AI Act questions

Gaps

Higher implementation coordination
You must define which tool owns which control

Architecture

A realistic compliance stack

Multi-framework GRC, including GDPR

Category: GRC platform

Example: Vanta, Drata or Secureframe

AI inventory, policy, and governance system of record

Category: Enterprise AI governance platform

Example: OneTrust, Credo AI, Holistic AI or IBM watsonx.governance

LLM development and debugging

Category: Observability platform

Example: LangSmith, Langfuse or Arize AI

Runtime governance and evidence

Category: Runtime control plane

Example: KLA (publisher of this guide)

Timeline

Practical timeline to the new deadlines

Now (October 2026)

Complete your AI inventory and classification.
Record your roles: provider or deployer under the AI Act, controller or processor under the GDPR.
Check Article 50 transparency, which has applied since 2 August 2026.

By 2 December 2026

Finish machine-readable marking of AI-generated content before the grace period ends.
Check your systems against the new Article 5 prohibitions that apply from that date.

Through 2027, toward 2 December 2027 (Annex III)

Complete technical documentation, oversight procedures, the FRIA where required, and evidence exports.
Providers: align the QMS with EN 18286:2026.
Run an audit-readiness drill against real workflow samples and retained evidence.

Toward 2 August 2028 (Annex I products)

Align AI Act evidence with the sectoral conformity assessment for the product.
Validate retention, export and post-market monitoring (Article 72) processes.

Decision

The decision, in one line

No single product covers governance strategy, surrounding-system evidence, developer observability and workflow-level runtime control. Name your system of record first, then decide whether your highest-risk workflows also need a runtime control plane. Push every vendor on three things: how deep their runtime control goes, how portable and verifiable their evidence is, and which features are generally available today.

Compliance and risk teams that also need traceable research behind a decision can look at Grep, which describes custom AI agents for due diligence, institutional onboarding and continuous monitoring.

Our own category, stated plainly: KLA is a runtime layer that sits alongside your GRC or AI governance platform. It evaluates each proposed agent action against policy in the execution path, routes high-stakes actions to human approval, and seals the evidence so an auditor can verify it.

If you are choosing a system of record, start with a governance platform. If you are choosing how to control and record high-risk AI actions, book a demo or read the pricing.

FAQ

Frequently asked questions

What's the best EU AI Act compliance software?: No product is best for every buyer. The software splits into four categories (GRC automation, enterprise AI governance, LLM observability and runtime control planes), and many regulated teams run two: a governance system of record, and a way to control and record what their highest-risk AI does in production. Score candidates with the evaluation worksheet on this page.
How do I choose compliance software for dual GDPR and EU AI Act readiness?: Start from your roles: controller or processor under the GDPR, provider or deployer under the AI Act. List the duties both laws give you: impact assessments (DPIA and FRIA), human review of automated decisions (GDPR Article 22, AI Act Article 14), records (GDPR Article 30, AI Act Articles 12 and 26(6)) and notices. Then ask each vendor to show one record that serves both regulators, and check its data-processing terms under GDPR Article 28.
Where can I buy compliance software for dual GDPR and EU AI Act readiness?: Buy directly from the vendor. Observability tools such as Langfuse, LangSmith and Arize publish self-serve price lists. GRC, enterprise AI governance and runtime control platforms sell through a scoped quote. Before signing, ask for an EU hosting region, a GDPR Article 28 data processing agreement, the sub-processor list and an export of your records on exit.
What is the cost of compliance software for GDPR and the EU AI Act?: Published October 2026 prices: Langfuse cloud from free to USD 2,499 a month and free to self-host; LangSmith Plus USD 39 per seat a month; Arize AX Pro USD 50 a month. KLA starts with a four-week SAFR Production Sprint from EUR 5,000. GRC and AI governance platforms quote per contract, so ask which unit they price by (seats, frameworks, AI systems or agents) and what year two costs.
What's the best EU AI Act compliance software for enterprises?: Enterprises with large AI portfolios usually start with an enterprise AI governance platform (OneTrust, Credo AI, Holistic AI, IBM watsonx.governance) as the system of record for discovery, classification and impact assessments. They add runtime control for the high-risk workflows where they must show human oversight (Article 14) and records an auditor can use (Article 12).
What's the best EU AI Act compliance software for startups?: If AI is one framework among SOC 2, ISO 27001 and GDPR, a GRC platform (Vanta, Drata, Secureframe) covers the most ground for one contract. If you ship a high-risk or agentic product, give priority to runtime control that records oversight on the decisions that carry regulatory exposure.
When does the EU AI Act high-risk deadline fall?: Regulation (EU) 2026/1744, the Digital Omnibus on AI, was published in the Official Journal on 24 July 2026 and has been in force since 27 July 2026. It moved stand-alone Annex III high-risk obligations, the Article 27 FRIA and Article 49 registration to 2 December 2027, and high-risk AI in Annex I products to 2 August 2028. Article 50 transparency duties have applied since 2 August 2026, and the grace period for marking AI-generated content ends on 2 December 2026.
Does EN 18286 change what I should buy?: On 14 October 2026 the Commission published the reference of EN 18286:2026, the quality management system standard for AI Act purposes, in the Official Journal (Implementing Decision (EU) 2026/2274). Providers that follow it get a presumption of conformity under Article 40 for the Article 17 requirements it covers. If you are a provider, ask vendors whether their QMS templates map to EN 18286 clauses.
Does KLA have a commercial interest in this guide?: Yes. KLA publishes this guide and sells KLA Control Plane, a runtime control plane. The other vendors are described from their own public pages as checked in October 2026. The guide does not rank vendors.

Links

Sources

EUR-Lex: Regulation (EU) 2024/1689 (Artificial Intelligence Act)

https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1689

Open

EUR-Lex: Regulation (EU) 2026/1744 (Digital Omnibus on AI)

https://eur-lex.europa.eu/eli/reg/2026/1744/oj/eng

Open

EUR-Lex: Implementing Decision (EU) 2026/2274 (EN 18286:2026 reference)

https://eur-lex.europa.eu/eli/dec_impl/2026/2274/oj

Open

BSI: EN 18286:2026 harmonized (14 October 2026)

https://www.bsigroup.com/en-GB/insights-and-media/media-centre/press-releases/2026/october/en-18286-2026-harmonized-a-significant-milestone-for-ai-act-compliance/

Open

EUR-Lex: Regulation (EU) 2016/679 (GDPR)

https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng

Open

European Parliament Legislative Observatory: Digital Omnibus 2025/0360(COD)

https://oeil.europarl.europa.eu/oeil/en/procedure-file?reference=2025/0360(COD)

Open

European Commission: AI Act implementation timeline

https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai

Open

Vanta: AI governance

https://www.vanta.com/products/ai-governance