European regulation governing the use of AI, classifying systems by risk level.

👉 Sovereign AIs must comply with its requirements.

Techniques aimed at protecting personal data. Anonymization makes re-identification impossible, while pseudonymization replaces certain attributes with identifiers.

U.S. law allowing authorities to access data hosted by U.S. companies, even if stored outside the country.

👉 Main risk of dependence outside the EU.

Cloud that complies with strict security (SecNumCloud, ISO 27001), governance, and sovereignty criteria.

Generative AI-based digital assistant, designed, trained, and hosted in a sovereign environment in France or Europe.
Unlike proprietary copilots offered by American hyperscalers, a French copilot ensures data confidentiality, non-submission to extraterritorial laws (Cloud Act, FISA), and compliance with European regulations (GDPR, AI Act).

👉 Tailored to the needs of public and private organizations handling sensitive data (healthcare, defense, research), it allows users to leverage the capabilities of AI co-pilots while ensuring the security and sovereignty of critical environments.

European framework for organizing data sharing in a trusted environment.

European regulation on the sharing and interoperability of industrial data.

Architecture that unifies security, governance, and interoperability across a multi-cloud or hybrid environment.

Architecture combining the flexibility of data lakes and the performance of data warehouses.

👉 Enables large-scale AI use cases without proprietary dependencies.

Complete traceability of a dataset, from its source to its use.

👉 Ensures compliance and auditability.

A decentralized approach where each business domain is responsible for its own data products.

Requirement for data to be physically located in a specific jurisdiction.

👉 Often required by the GDPR or health laws.

Open storage formats used to make data lakes more reliable and standardized.

European initiative launched in 2020 to create an ecosystem of interoperable, secure, and sovereign cloud data and services.
GAIA-X is not a cloud in itself, but a framework of standards and labels designed to ensure that cloud infrastructures and services comply with principles of transparency, portability, and European compliance (GDPR, security, interoperability).

👉 For strategic sectors, GAIA-X represents a credible alternative to the monopoly of American hyperscalers, promoting a trusted cloud based on European cooperation.

French certification guaranteeing the security and confidentiality of medical data.

Deployment and operation of generative AI models (LLMs, diffusion models, copilots) in a cloud infrastructure certified SecNumCloud by ANSSI. This approach ensures that the data used for training, adapting, or inferring models is protected within a sovereign and highly secure framework.

👉 It meets the sovereignty and compliance requirements of strategic sectors (healthcare, defense, public services), offering the power of generative AI without exposure to extraterritorial risks (Cloud Act, FISA).

Use of Generative AI (LLM, RAG, agents, etc.) on internal infrastructure or a sovereign private cloud.

👉 Confidentiality guarantee for sensitive environments.

Use of Generative AI (LLM, RAG, agents, etc.) in a framework that is immune to extraterritorial laws, enabling data protection.
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👉 Complies with GDPR and AI Act requirements.

Set of practices for deploying, monitoring, and securing AI models in a certified environment.

Centralized management of reference data (customers, products, etc.).

Data migration to a SecNumCloud-certified infrastructure.

👉 Key step in modernizing without compromising security.

European directive strengthening cybersecurity obligations for operators of essential services.

Pipeline automation (ETL/ELT) using tools such as Airflow or Dagster.

Data management and operating environment deployed directly on an organization's internal infrastructure (local servers, private data center). It provides total control over data security, governance, and location, without dependence on an external public cloud.👉 Preferred solution for strategic sectors (defense, healthcare, research, etc.) requiring total control over their sensitive data.

An integrated approach that avoids the complexity and fragmentation of the modern data stack.

Comprehensive environment (ingestion, storage, governance, analytics, AI) operated within a sovereign framework.

👉 Strategic alternative to American platforms.

Software environment for designing, deploying, and orchestrating intelligent agents (autonomous generative AI, multi-agent workflows) directly on an organization's internal infrastructure, without the need for a public cloud.
These platforms combine models (LLMs, RAG engines, planning tools) with local orchestration to automate complex tasks: document analysis, report generation, business process management.

👉 In the on-premise version, they guarantee data confidentiality, complete control over models, and compliance with regulatory requirements (GDPR, SecNumCloud, AI Act). This is a key option for strategic sectors (defense, healthcare, energy, public services) that want to leverage agentic AI without external dependencies.

Platform for the design, industrialization, and management of agents based on generative AI technologies, providing data protection guarantees and expertise within a sovereign framework (European technologies, LLM, and hosting).

Technique combining search engine + LLM hosted in a sovereign framework.

European regulation governing the collection and processing of personal data of EU citizens.

👉 Essential standard for any data project.

Practices aimed at making AI ethical, reliable, and compliant with regulations.

Certification standard issued by ANSSI, setting security and governance requirements for cloud providers. In particular, it requires data to be located in Europe and protected against extraterritorial laws.

The ability of a state or organization to maintain control over its data, infrastructure, and technologies.

👉 Key concept for strategic sectors facing dependence on GAFAM.

“Never trust, always verify” security model, where every access must be authenticated, authorized, and encrypted.