Governance & Quality
Structure the governance of your data and your AI uses.
The AI Act is in effect. Are your AI uses documented, classified and compliant? We set up Data and AI governance frameworks that protect you from the regulator, secure your data and build trust with your customers and partners.
+150 companies supported
— 5/5 Google reviews
Benefits/Impacts
What it brings
Concrete results for your organization, measurable from the first weeks of intervention.
01
Regulatory compliance before sanctions
Your AI systems are classified by risk level, documented and audited according to the requirements of the AI Act. You're ready when the controller knocks on the door, not after.
02
Complete traceability of your data and models
Who accessed what data, which model made what decision, on what basis. Each action is traced, documented and auditable.
03
The trust of your stakeholders
Customers, partners, investors, and management committees: everyone wants guarantees about how you use AI and data. Governance transforms reputational risk into competitive advantage.
04
Teams that know what they are allowed to do
No more gray areas. Each business has clear rules on the use of data and AI, with defined validation processes and assigned responsibilities.
05
Governance that does not hinder innovation
The framework we are putting in place is designed to secure without paralyzing. Data and AI teams can continue to move quickly, within a controlled perimeter.
Chapters
Our expertise
The skills and know-how that we mobilize to deliver results on this expertise.
Tools/Partnership
How do we implement this expertise
We rely on proven governance methodologies and market tools, while adapting each device to the size, sector and maturity of your organization. No theoretical framework stuck: an operational framework that works.
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
Type of projects
What we deliver
Operational deliverables, not recommendations. Here are the mission formats that we deploy on this expertise.
01
AI Act compliance audit
Complete inventory of your AI uses, classification by risk level, analysis of differences with regulatory requirements and a 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 the rules for the development, validation and production of AI models: validation committee, mandatory documentation, bias monitoring and approval circuit.
04
RGPD compliance of Data & AI treatments
Audit of existing treatments, register of treatments, impact analyses (DPIA) on high-risk AI systems and implementation of rights management processes.
Business Cases
They structured their Data & AI governance with us
We do not deliver POCs. We deliver systems that work, with a measurable impact on the business of our customers.
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 do I comply with it?
The AI Act is the European regulation that classifies and regulates AI systems according to their level of risk, with obligations of documentation, transparency and human supervision. Diametral delivers an AI Act audit in 6 to 10 weeks that maps your AI uses, identifies high-risk systems and deploys the compliance plan.
What does a Data & AI governance program contain?
A governance program covers data access policies, quality, model traceability, human supervision, bias management, and regulatory documentation. Diametral structures these elements in 3 to 6 months via a clear operating 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 blocking it by providing a clear framework for teams to experiment without risk. Diametral designs supervised sandboxes where Data Scientists quickly test models, then apply compliance checkpoints before going into production.
What is the difference between Data Governance and AI Governance?
Data governance covers data quality, access, and traceability, while AI governance also addresses algorithmic biases, human supervision, and AI Act compliance. Diametral deploys both layers consistently because compliant AI without governed data remains exposed to regulatory risks.
contact
Are you ready for the AI Act?
A quick diagnosis to assess your regulatory exposure and identify the first actions to launch.