Governance & Quality
Structure the governance of your data and AI applications.
The AI Act is now in force. Are your AI practices documented, classified, and compliant? We implement Data and AI governance frameworks that protect you from regulatory audits, secure your data, and strengthen the trust of your clients and partners.
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Benefits / Impacts
What it delivers
Concrete results for your organization, measurable within the first few weeks of intervention.
01
Regulatory compliance before penalties
Your AI systems are classified by risk level, documented, and audited according to the requirements of the AI Act. You are ready when the regulator comes knocking, not after.
02
Complete traceability of your data and models
Who accessed which data, which model made which decision, and on what basis. Every action is tracked, documented, and auditable.
03
The trust of your stakeholders
Clients, partners, investors, and the board of directors: everyone wants assurances on how you use AI and data. Governance transforms a reputational risk into a competitive advantage.
04
Teams that know what they are allowed to do
No more grey areas. Each department has clear rules on the use of data and AI, with defined validation processes and assigned responsibilities.
05
Governance that doesn't stifle innovation
The framework we implement is designed to provide security without hindering progress. Data and AI teams can continue to move quickly within a controlled scope.
Chapters
Our Expertise
The skills and know-how we leverage to deliver results in this area of expertise.
Tools / Partnerships
How We Apply This Expertise
We leverage proven governance methodologies and industry-standard tools, tailoring each approach to your organization's size, sector, and maturity. No rigid theoretical framework: just a practical framework that delivers results.
Amazon Web Services
Google Cloud
Azure
Apache Airflow
Power BI
Amazon Web Services
Google Cloud
Azure
Apache Airflow
Power BI
Amazon Web Services
Google Cloud
Azure
Apache Airflow
Project Types
What We Deliver
Actionable deliverables, not just recommendations. Here are the engagement formats we offer for this expertise.
01
AI Act Compliance Audit
Complete inventory of your AI uses, classification by risk level, gap analysis against regulatory requirements, and prioritized remediation plan. Delivered in 6 to 10 weeks.
02
Data Governance Program
Implementation of the complete organizational framework: roles and responsibilities, data policies, quality standards, cataloging tools, and control processes. Deployment in 3 to 6 months depending on the scope.
03
AI Governance Framework
Definition of rules for the development, validation, and deployment of AI models: validation committee, mandatory documentation, bias monitoring, and approval workflow.
04
GDPR compliance for Data & AI processing activities
Audit of existing processing activities, processing register, impact assessments (DPIAs) on high-risk AI systems, and implementation of rights management processes.
Business Cases
They structured their Data & AI governance with us
We don't deliver POCs. We deliver working systems with a measurable impact on our clients' business.
Your questions, our answers
All the answers to understand our approach, how we work, and what you can expect from our collaboration.
What is the AI Act and how to comply with it?
The AI Act is the European regulation that classifies and regulates AI systems according to their risk level, with obligations for documentation, transparency, and human oversight. Diametral delivers an AI Act audit in 6 to 10 weeks that maps your AI uses, identifies high-risk systems, and implements the compliance plan.
What does a Data & AI governance program include?
A governance program covers data access policies, quality, model traceability, human oversight, bias management, and regulatory documentation. Diametral structures these elements within 3 to 6 months through a clear operational model, defined Data Owner and AI Steward roles, and regular review committees.
How long does an AI Act audit take?
An AI Act Diamétral audit lasts 6 to 10 weeks depending on the number of AI systems to be analyzed. The deliverable includes a risk-by-use classification, a list of compliance gaps, a prioritized action plan, and pre-filled regulatory documentation templates to accelerate effective compliance.
How to reconcile AI governance and innovation?
Good governance accelerates innovation instead of hindering it, by providing a clear framework for teams to experiment without risk. Diametral designs supervised sandboxes where Data Scientists can quickly test their models, then applies compliance checkpoints before moving to production.
What is the difference between Data Governance and AI Governance?
Data governance covers data quality, access, and traceability; AI governance also addresses algorithmic bias, human oversight, and AI Act compliance. Diametral deploys both layers coherently, because compliant AI without governed data remains exposed to regulatory risks.
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Are you ready for the AI Act?
A quick diagnostic to assess your regulatory exposure and identify initial actions to take.