AI Compliance

Data Governance

The global regulatory framework for artificial intelligence is tightening rapidly: the European Union AI Act (EU AI Act), LGPD in Brazil, US regulatory frameworks, and local privacy laws impose multimillion-dollar fines and potential operation bans on enterprises deploying AI systems without verified compliance.

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Description

We ensure end-to-end regulatory compliance for your AI systems (AI Compliance). We classify applications across regulatory risk tiers, draft mandatory technical documentation (Model Cards, System Cards), implement strict privacy safeguards (PII redaction via Presidio), and ensure full readiness for official regulatory inspections.

As a specialized capability, Data Governance provides a focused approach to the technical and strategic requirements of the AI Compliance domain. We design custom operational protocols, implement rigorous validation, and give the organization full control over this critical factor to secure a sustainable competitive advantage across the language model and generative AI ecosystem.

Impact Thesis & Return on Investment

Business continuity and friction-free access to high-value international markets (such as the EU and the United States), elimination of draconian fines, and competitive advantage by showcasing trustworthy, ethical AI certifications. In today's corporate ecosystem, securing presence and accuracy across foundation models is not merely a competitive advantage, but a critical defensive barrier against the disintermediation of traditional digital traffic.

Methodology

Mapping of applicable legal obligations across jurisdictions and use cases; audit of training and context data; automated anonymization and masking of personal data; generation of Model Cards aligned with IEEE and EU standards.

Technology Stack

Technology Ecosystem: Microsoft Presidio (PII Redaction), EU AI Act Compliance Framework, HuggingFace Model Cards, OneTrust, OpenPrivacy.
Semantic Standards: W3C Semantic Web Standards, Schema.org @graph, RDF/OWL ontologies, OpenAPI 3.1.
Validation Protocols: Continuous evaluation with LLM-as-a-Judge, semantic guardrails, and regression tests in continuous integration pipelines.

Deliverables

Regulatory risk classification assessment under the EU AI Act and local regulations.
Mandatory technical documentation dossier (System Card and Model Card).
Personal data anonymization and masking module for inference pipelines.
Record of personal data processing activities within AI models.

Success KPIs

100% compliance with documentary and technical requirements of applicable regulations.
0% personally identifiable information (PII) leaked or improperly stored in inference logs.
Regulatory audit readiness certification across target geographic markets.
Approval without reservations by corporate legal departments.

Who is it for?

Who it is for

Software exporters targeting Europe or the US, multinationals, fintechs, and organizations handling sensitive personal data.

Who it is NOT for

Simple domestic projects without personal data processing or international expansion goals.

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