EU AI Act
AI Act Compliance — Govern production AI end to end
The EU AI Act raises the bar on risk management, traceability, human oversight, and documentation. Argy helps you operationalize these controls from day one: usage policies, audit trail, approvals, and standardized paths on your tools.
Quick access
Note: this page is not legal advice. It describes a product and operational approach.
What changes with the EU AI Act
The EU AI Act sets obligations based on risk (e.g., prohibited practices, high-risk systems, transparency obligations). In practice, organizations must be able to demonstrate:
- • A governance framework (roles, approvals, responsibilities).
- • Risk management and controls aligned with each use case.
- • Sufficient documentation and traceability (decisions, logs, evidence).
- • Human oversight, robustness, and incident handling.
Argy acts as the industrialization and governance layer: you standardize the “how” (golden paths), control the “who/what/why” (policies, RBAC, audit), and produce reusable evidence.
Argy: governance & compliance by design
A platform to deploy AI use cases under control—on your tools and constraints.
Usage policies (LLM Gateway)
Centralize rules: allowed models, limits, contexts, and guardrails. Explore the LLM Gateway.
Traceability & audit trail
Track key actions and decisions to support audits and continuous improvement (with exports for your tools).
RBAC & approvals
Enforce least privilege, separate duties, and add human validations for sensitive actions.
Key controls (AI Act mapping)
You should tailor controls to your risk classification and use cases. Here is how Argy helps operationalize common requirements.
1) Governance, responsibilities, oversight
- • RBAC and role separation (admin, approver, users).
- • Approval workflows for sensitive AI usage and actions.
- • Human-in-the-loop: explicit validation in critical paths.
2) Usage controls: policy-as-code
- • Centralized rules for model access and capabilities (quotas, restrictions, scopes).
- • Reduce “shadow AI” by offering an official governed path.
- • Align with internal standards (allowed data, sensitive fields, security requirements). LLM Gateway.
3) Traceability, logs, audit evidence
- • Audit trail of actions and events (who did what, when, in which context).
- • Exports for reporting and integrations (e.g., SIEM / GRC) as needed.
- • Faster audit prep: standardized, repeatable evidence.
4) Technical documentation & industrialization
- • Standardize delivery through reusable modules and automations.
- • Reduce variance with “golden paths” instead of ad hoc implementations.
- • Enablement through your documentation. See the docs.
Evidence & deliverables (audit-ready)
A large part of AI Act work is proving, over time, that controls are applied and decisions are traceable. Argy makes it easier to produce actionable evidence:
- • Action history (audit trail) and event exports.
- • Usage policies and configurations (versioned and reviewed).
- • Roles, permissions, approvals, and responsibilities.
- • Standardized delivery paths (modules/automations) to reduce operational risk.
For a broader product overview: explore Argy or view pricing.
Getting started
We start from your use cases (and your risk classification), then put AI flows under control: policies, roles, traceability, and standardized delivery paths.
European SaaS
GDPR compliant & hosted in EU
No Lock-in
Built on open standards
API-First
Everything is automatable
Ready to turn AI into an enterprise operating system?
Share your context (toolchain, constraints, org). We’ll propose a pragmatic rollout that makes AI governed, scalable, and sovereign.