How NexusFinLabs turns continuous adversarial red-teaming into demonstrable compliance with Regulation (EU) 2024/1689 — for generative-AI customer-service and decision-support systems operating in Spanish and English across the EU market.
Independent research now makes one thing clear: production GenAI systems are routinely exploitable, and single-try validation creates false confidence. Most teams can already say something about “is our GenAI secure?” The adjacent question every EU deployment must also answer is “can we prove it to a regulator?”
The EU AI Act makes that question mandatory. Robustness and cybersecurity testing is no longer just good practice — for many systems it is a legal obligation with evidence requirements. NexusFinLabs produces exactly that evidence through adversarial red-teaming, and then maps, documents and localizes it to the obligations that apply to your system.
Penalties scale with the breach: up to €35M or 7% of worldwide annual turnover for prohibited practices, up to €15M or 3% for breaching other obligations, and up to €7.5M or 1% for supplying incorrect information. For customer-facing assistants, two duties bite early: Art. 50 transparency (users must be told they are interacting with an AI), and, where the system supports a regulated decision, the full high-risk regime, including Art. 15 accuracy, robustness and cybersecurity — explicitly covering resilience to adversarial manipulation.
Where the system sits in the Act's tiers (prohibited / high-risk / limited-risk transparency / minimal), and which obligations follow. A clear, defensible classification with rationale.
Adversarial test results — prompt injection, jailbreak, data leakage, PII exposure — mapped to the accuracy / robustness / cybersecurity requirements, with reproducible findings.
AI-interaction disclosure and, where relevant, AI-generated-content marking — checked against the limited-risk transparency duties.
Technical documentation, logging, human-oversight design and risk-management process — aligned with the Act and cross-referenced to the NIST AI RMF and ISO/IEC 42001.
Red-teaming is the engine; readiness is the dossier. We continuously generate the adversarial evidence at scale, map it to the Act, fill the governance gaps, and localize the whole thing for the Spanish / EU context — turning a security capability into an audit-ready compliance posture.
| AI Act obligation | What it needs | How NexusFinLabs covers it |
|---|---|---|
| Art. 15 — robustness & cybersecurity | Evidence of resilience to adversarial inputs & manipulation. | Adversarial red-team runs, mapped to the article, scored & reproducible. |
| Art. 9 — risk management | Ongoing, documented risk process. | Continuous testing feeds a living risk register; we author the process docs. |
| Art. 50 — transparency | Disclose AI interaction; mark AI content. | UX & system-prompt review against the duty; remediation list. |
| Art. 12 / 14 — logging & oversight | Traceability and human control. | Logging & oversight design reviewed and gap-listed. |
| Localization (ES / EU) | Tests & controls valid in-language. | Native Spanish & English adversarial coverage — where English-first tooling underperforms. |
Risk tier, applicable articles, threat surface in ES & EN.
Adversarial tests against the live system; collect evidence.
Findings → AI Act articles; readiness scorecard & gap list.
Priority fixes, monitoring plan, CI gate for ongoing proof.
Per-article status (ready / gap / N/A) with a defensible risk classification.
Reproducible adversarial findings, severities and the system's actual responses.
Prioritized actions, owners and a monitoring / re-test cadence.
A real scan against a sample agent, in ES & EN — see nova / live scan.
This document provides assurance and readiness guidance, not legal advice, and does not constitute certification or a conformity assessment under Regulation (EU) 2024/1689. Dates and penalty figures reflect the Regulation as published; confirm applicability for your specific system with qualified counsel.