EU AI Act High‑Risk AI Compliance Services (Readiness & Implementation)

High‑risk requirements under the EU AI Act are triggered when your AI system is considered "high‑risk" under the Act's framework. This can include (a) AI systems that are safety components of products covered by EU harmonisation legislation (such as certain regulated products), and (b) AI systems in specific use cases listed as high‑risk (Annex III).^[3]

Many teams seek external support when they:

• Need to classify whether their AI system falls into high‑risk categories and map the obligations;
• Must stand up governance processes (risk management, documentation, monitoring) quickly ahead of applicability dates;
• Want a provider who can deliver concrete artifacts (policies, templates, technical documentation structure, training, and audit prep).

Timing note: The AI Act applies in stages; the entry-into-force and application schedule is defined in the Act.^[2] Some obligations tied to high‑risk AI systems associated with regulated products apply later (e.g., from 2 Aug 2027 for certain provisions).^[2] Your RFQ should include your target market date and whether you are integrating AI into a regulated product or standalone service.

Important: "High‑risk" determination can be nuanced. This directory helps you compare providers who can support classification, documentation, and operational implementation—but you should validate the final interpretation against the legal text and your facts.

High‑risk AI compliance projects are usually delivered as a defined package (4–12 weeks) or an ongoing retainer. Providers often bundle governance, documentation, and operational processes.

Common deliverables:

• Risk classification + applicability memo (high‑risk basis and actor roles);
• AI risk management system (hazard/risk identification, controls, acceptance criteria, and review cadence);
• Data governance approach (quality, relevance, bias considerations, lineage documentation);
• Technical documentation structure (what to document, how to maintain it, versioning);
• Human oversight design and operating procedures;
• Logging and traceability requirements mapping (what logs, retention, access);
• Post‑market monitoring plan and incident response workflows;
• Conformity assessment support (process preparation, evidence collection, audit readiness).

For teams in regulated products, many providers also align AI Act work with existing QMS and product compliance processes (e.g., documented controls, design change governance), but the exact integration depends on your sector and product type.

High‑risk AI compliance support is priced like a transformation project: the fee reflects scope, artifact production, and cross-functional effort.

• System complexity: number of models, pipelines, release cadence, and integration points;
• Evidence readiness: existing documentation maturity (if you have nothing, providers must build a lot);
• Domain risk: higher-impact sectors typically require deeper process rigor and stakeholder alignment;
• Delivery timeline: 2–4 week "sprint" delivery costs more than 8–12 week delivery;
• Conformity assessment support: preparation + audit support can significantly increase scope;
• Ongoing monitoring: post‑market monitoring and incident response retainers add recurring cost.

Practical tip: Make RFQs comparable by asking for (a) fixed-price readiness package, (b) optional ongoing retainer, and (c) a deliverables list (artifacts + workshops + handover).

Look for providers who can produce concrete compliance artifacts and help operationalize them.

• Interpretation capability: can they map your system to the AI Act framework and explain why it is (or isn't) high‑risk?
• Artifact delivery: ask for sample deliverables (templates, doc structures, governance playbooks).
• Engineering + governance fluency: they should work smoothly with legal/compliance and technical teams.
• Implementation realism: avoid "paper compliance" that won't survive audits or operational use.
• Security posture: you may need to share sensitive model details—check secure handling.
• Change management: ask how they build sustainable processes for releases and ongoing monitoring.

Red flags: providers who promise guaranteed outcomes, can't explain assumptions, or won't define deliverables and acceptance criteria.