Compliance
Guardrails & audit trails for the EU AI Act
The EU AI Act entered into force in August 2024 and becomes fully applicable on 2 August 2026, with obligations phasing in along the way. Its reach is extraterritorial: it applies to providers and deployers outside the EU when their systems or outputs are used in the EU, with penalties up to €35 million or 7% of global revenue.
For teams running LLM applications and agents, the practical weight lands on a few recurring themes: risk management as a process, logging and traceability, human oversight over consequential operation, and accuracy and robustness controls. These are runtime properties – and runtime is what a guardrails proxy instruments.
The honest part, up front: no tool makes you compliant. Compliance is a property of your organization – its processes, contracts, and documentation – not of any component you install. What a guardrails proxy provides is technical measures and evidence that support the obligations below. Assess your own obligations with counsel.
Logging & traceability – high-risk systems must automatically record events over their lifetime, and deployers must retain logs (six months at minimum under Articles 19 and 26)
Every request records which checks ran, their verdicts, timings, and costs; agent runs reconstruct into complete traces across model calls, tool calls, and workflow checkpoints. Retention is a plan setting; screened-by-default logging keeps the archive itself low-risk.
Human oversight – Article 14 requires systems be designed so humans can effectively oversee them, understand behavior, and intervene
Approval tiers put a human decision in front of designated actions (a payment, a deletion) via the checkpoint API; the run graph makes what the agent actually did legible to the person overseeing it; PREVENT mode is the intervention path, enforced in line.
Accuracy & robustness – Article 15 requires appropriate accuracy, robustness, and cybersecurity, resilient to errors and manipulation attempts
Grounding and fact-checking measure and enforce output accuracy per request; injection defense addresses the manipulation channel unique to LLMs; format enforcement and fail-closed behavior contain error propagation.
Risk management – Article 9 requires an iterative risk-management process across the lifecycle
Observe-then-enforce is that loop, instrumented: run checks in FIX mode to measure risk on real traffic, review findings, tighten to PREVENT where evidence warrants – with the dashboard as the record of the process.
Transparency to deployers – systems used with or affecting people carry information duties
Response headers and per-request reports state what was checked and what was found – machine-readable evidence your application layer can surface as its transparency obligations require.
Does using a guardrails proxy make my AI system EU AI Act compliant?
No – and no product honestly can. Compliance involves classification, documentation, conformity assessment, and organizational processes. The proxy contributes technical measures (logging, oversight hooks, robustness controls) and the per-request evidence that your documentation can cite.
Are most LLM applications “high-risk” under the Act?
Most are not – the high-risk category is defined by specific use areas (Annex III) such as employment, credit, and essential services. But the Act’s logging, transparency, and oversight themes are becoming the de-facto bar customers expect, whatever your classification. Classify with counsel.
What does the Act say about general-purpose AI models?
GPAI obligations (transparency, copyright policy, training-data summaries) fall mainly on model providers, with obligations phasing from August 2025. As a deployer building on those models, your duties concentrate on how you use them – which is the layer the proxy instruments.
How does the six-month log retention interact with data minimization?
This is exactly why screened-by-default logging matters: transcripts are stored with PII replaced by placeholders, so retaining operational logs for traceability does not mean warehousing personal data. Raw logging remains a deliberate, audited opt-in.
Bring your compliance team to the demo.
The per-request evidence trail tends to answer their questions faster than a slide deck. We’re running a limited demo – sign up and we’ll get you in as soon as we can.