Annex IV Technical Documentation: A Practical Guide

Why Annex IV Matters

If your AI system is classified as high-risk under the EU AI Act, one of your most significant obligations is the preparation of technical documentation in accordance with Annex IV of the regulation. This documentation must be prepared before the system is placed on the EU market or put into service, and it must be kept up to date throughout the system's lifecycle.

Technical documentation serves a dual purpose: it demonstrates to authorities and notified bodies that your system meets the requirements of the regulation, and it provides deployers (your customers) with the information they need to use the system safely and in compliance with the law.

This guide breaks down each section of Annex IV, explains what is required in practical terms, and provides tips for efficient documentation preparation.

The Structure of Annex IV

Annex IV requires documentation covering the following areas. The documentation must be drawn up before the system is placed on the market or put into service, and must be kept up to date.

Section 1: General Description of the AI System

This section establishes the system's identity and purpose. You must document:

• Intended purpose: A clear, specific description of what the system is designed to do. This is not a marketing description — it must be precise enough to determine the system's risk classification and applicable requirements.
• Provider identity: Name, address, and contact details of the provider (and authorized representative, if applicable).
• Version identification: How the system is identified and versioned, including software version numbers.
• Hardware requirements: Any hardware on which the system is intended to run, if relevant.
• Product integration: If the system is a component of a product, a description of how it integrates and the product's CE marking information.
• Interaction with other systems: How the AI system interacts with other hardware or software, including APIs, data flows, and system dependencies.

Practical tip: Start with your product specification documents and engineering design records. Much of this information already exists — it just needs to be organized into the Annex IV structure.

Section 2: Detailed Description of System Elements and Development Process

This is the most technically detailed section. It requires:

• Development methods and techniques: The methodologies used to develop the system, including model architecture, training approaches, and design choices.
• Design specifications: The system's architecture, including data flow, computational logic, and algorithmic principles.
• System architecture: A description of how the system's components interact, including model pipelines, pre-processing, post-processing, and integration layers.
• Computational resources: The computational resources used for development, training, testing, and validation (including hardware specifications and cloud infrastructure details).
• Third-party components: Any pre-trained models, third-party tools, libraries, or datasets used, including their versions and license terms.
• Key design choices: The rationale behind significant design decisions, including trade-offs considered.

Practical tip: This section requires close collaboration between your engineering team and your compliance team. Establish a documentation process that captures these details during development, not after. Our document generator auto-populates much of this from your AI system registry data.

Section 3: Detailed Information About the Monitoring, Functioning, and Control of the AI System

This section covers the system's operational behavior:

• Capabilities and limitations: What the system can and cannot do, including known limitations, foreseeable misuse scenarios, and the conditions under which the system may not perform as expected.
• Levels of accuracy, robustness, and cybersecurity: The system's performance characteristics, including accuracy metrics, robustness under adversarial conditions, and cybersecurity protections (aligned with Article 15).
• Human oversight measures: How human oversight is implemented (aligned with Article 14), including the tools, interfaces, and procedures that allow humans to monitor, intervene in, or override the system's outputs.
• Specifications for input data: What data the system expects as input, including format, quality requirements, and any constraints.

Section 4: Risk Management System Documentation

Article 9 requires a risk management system for high-risk AI systems. Annex IV requires documentation of this system, including:

• The risk management process and methodology
• Identified risks and their assessment
• Risk mitigation measures implemented
• Residual risks and their acceptability
• Ongoing monitoring and review procedures

This documentation must demonstrate a continuous, iterative process — not a one-time assessment.

Section 5: Data and Data Governance

This section documents your data practices, aligned with Article 10:

• Training data: Description of training datasets, including origin, scope, characteristics, availability, quantity, and the processes used to collect and prepare data.
• Data quality measures: Techniques used to ensure data quality, identify biases, and address data gaps.
• Validation and testing data: Description of the datasets used for validation and testing, and the methodology for their selection.
• Data governance practices: Policies and procedures for data management throughout the system lifecycle.

For AI systems processing personal data, this section must also address GDPR compliance, including the legal basis for processing and any Data Protection Impact Assessments conducted.

Section 6: Testing and Validation

Annex IV requires comprehensive documentation of testing:

• Testing procedures: The methodologies used to test and validate the system, including metrics, benchmarks, and test protocols.
• Test results: Actual performance results, including accuracy, precision, recall, and any other relevant metrics.
• Performance across subgroups: Testing results broken down by relevant demographic or contextual subgroups to identify potential biases or disparate impacts.
• Adversarial testing: Results of robustness testing, including adversarial attacks and edge case analysis.
• Validation methodology: How the system was validated against its intended purpose and real-world conditions.

Section 7: Changes and Modifications

Technical documentation must be a living document. You must maintain records of:

• All changes made to the system after initial documentation
• The impact assessment of each change on the system's compliance status
• Updated test results following significant modifications
• Version history with clear traceability

Common Pitfalls and How to Avoid Them

Pitfall 1: Treating Documentation as an Afterthought

The most common mistake is trying to create Annex IV documentation after the system is already developed and deployed. This leads to gaps, inconsistencies, and enormous effort to reconstruct information. Solution: Integrate documentation into your development process. Capture information as the system is built.

Pitfall 2: Insufficient Detail on Data Governance

Regulators will scrutinize your data practices closely, especially for bias and representativeness. Vague statements like "we use high-quality data" are insufficient. Solution: Document specific data sources, collection methods, preprocessing steps, quality metrics, and bias assessments.

Pitfall 3: Missing Performance Disaggregation

Reporting overall accuracy is not enough. Annex IV expects performance metrics broken down by relevant subgroups. Solution: Design your testing framework to capture disaggregated metrics from the start.

Pitfall 4: Static Documentation

Annex IV documentation must be maintained throughout the system's lifecycle. A document that was accurate at launch but has not been updated to reflect changes is non-compliant. Solution: Implement a documentation update process triggered by system changes, and maintain version control.

How Haffa.ai Helps

Our platform automates much of the Annex IV documentation process:

• Auto-populated templates: Register your AI system once, and our document generator creates Annex IV documentation pre-filled with your system data.
• Version control: All documents are version-controlled with complete change history.
• Compliance mapping: Each section maps directly to the relevant Articles and Annex IV requirements.
• Export formats: Generate documentation in PDF, Word, and structured data formats for regulatory submission.
• Automated updates: When you update your AI system registry, documentation flags sections that may need revision.

Start with a free risk assessment to determine your documentation obligations, or see our plans for access to the full documentation generator.