Shape the Future of your Business with Artificial Intelligence
Proximus NXT supports you in deploying AI within your organization, regardless of your stage in the AI journey, from strategic vision to adoption. Boost your productivity and discover how to integrate AI securely and in compliance to meet the specific needs of your business.
Solutions to power your AI transformation
Artificial intelligence is a powerful transformation lever, but its implementation requires a structured approach tailored to your digital maturity. Proximus NXT supports you at every step with secure solutions adapted to your industry.
End-to-End Support for your AI integration
Proximus NXT manages the entire lifecycle of your AI project, from defining your strategic vision to implementation and adoption of the solution by your teams. Our approach guarantees personalized support aligned with your business objectives.
Security and Compliance with AI regulation
Data governance and regulatory compliance are top priorities. Our AI solutions adhere to the strictest standards such as GDPR, CSSF, and ISO 27001. We ensure secure and transparent data management while hosting it in infrastructures that comply with European requirements.
Advanced AI Technology Expertise
Our AI experts develop tailored solutions incorporating the latest advancements in artificial intelligence: machine learning, natural language processing, computer vision, and intelligent automation. These technologies optimize your processes, improve customer experience, and enhance your business's competitiveness.
AI Visioning Services
Helping organizations envision and strategize the implementation of AI technologies to meet their specific goals.
AI Readiness Services
Assessing an organization's current capabilities and preparing them for successful AI adoption.
AI Application Development: On-Premises and Cloud
Developing AI applications that can be deployed both on-premises and in the cloud according to organizational needs.
AI Model Refinement
Improving and fine-tuning AI models to enhance their accuracy and efficiency.
M365 AI Solutions
Integrating AI capabilities with Microsoft 365 to enhance productivity and user experience.
AI Cloud Infrastructure
Setting up and managing cloud infrastructure to support scalable AI solutions.
AI Data Readiness
Ensuring data quality and accessibility to facilitate effective AI model training and deployment.
AI Training
Providing training programs to enhance the skills of individuals and teams in AI technologies and methodologies.
AI Visioning Services
Helping organizations envision and strategize the implementation of AI technologies to meet their specific goals.
AI Application Development: On-Premises and Cloud
Developing AI applications that can be deployed both on-premises and in the cloud according to organizational needs.
M365 AI Solutions
Integrating AI capabilities with Microsoft 365 to enhance productivity and user experience.
AI Data Readiness
Ensuring data quality and accessibility to facilitate effective AI model training and deployment.
AI Readiness Services
Assessing an organization's current capabilities and preparing them for successful AI adoption.
AI Model Refinement
Improving and fine-tuning AI models to enhance their accuracy and efficiency.
AI Cloud Infrastructure
Setting up and managing cloud infrastructure to support scalable AI solutions.
AI Training
Providing training programs to enhance the skills of individuals and teams in AI technologies and methodologies.
Our expertise on Azure AI Development
Create with advanced models designed for complex problem-solving, reasoning, and extended conversations. They’re ideal for tasks like code generation, math, and scientific inquiries.
Azure OpenAI Service is powered by a diverse set of models with different capabilities and price points. Model availability varies by region and cloud. For Azure Government model availability, please refer to Azure Government OpenAI Service.
Our expertise on GDCA AI Developement
GDC offers a generative AI search packaged solution enabled by Gemma, our state-of-the-art open models. The solution is designed to help customers easily retrieve and analyze data at the edge or on-premises with GDC. The generative AI search packaged solution is a ready-to-deploy on-prem conversational search solution that uses the Gemma 7B model.
Our AI transformation project methodology
The successful implementation of artificial intelligence solutions relies on a methodical and structured approach. At Proximus NXT, we have developed a proven methodology that supports our clients at every stage of their AI project, from identifying needs to the continuous optimization of deployed models.
This approach ensures smooth integration, effective adoption by teams, and compliance with industry and regulatory requirements.
- Exploration and Framing – Defining objectives and relevant use cases.
- Readiness Assessment – Analyzing governance, data, and infrastructure.
- AI Solution Deployment – Implementation, testing, and validation of AI models.
- Adoption and Training – Training teams and supporting change management.
- Monitoring and Continuous Improvement – Maintenance and updating of AI solutions.
Security and AI Regulation Compliance
Security and compliance are at the heart of any successful AI adoption. At Proximus NXT, we are committed to ensuring that your AI solutions comply with current regulations while providing optimal protection for your data.
- Compliance with GDPR, CSSF, and ISO 27001 standards.
- Data and AI model security protocols.
- Risk management and regular AI system audits.
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An organization's readiness for AI adoption is influenced by several key factors, including:
- the maturity of its digital infrastructure,
- the quality and accessibility of its data,
- the presence of clear governance structures,
- and the organization's culture toward innovation and change.
A readiness assessment typically evaluates whether:- the necessary skills,
- data frameworks,
- and strategic alignment
are in place to support AI initiatives effectively. Preparing the organization also means ensuring that teams are equipped to collaborate with AI systems and that security and compliance foundations are firmly established.
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Building an AI strategy begins with a clear understanding of the organization's business objectives and challenges. Businesses should start by identifying high value use cases where AI can deliver tangible outcomes, such as increased efficiency, enhanced decision-making, or improved customer experiences.
A structured approach involves framing a long-term vision, aligning stakeholders, prioritizing projects based on feasibility and impact, and establishing a governance model for responsible AI deployment. Scalability, security, and integration with existing systems must be considered from the outset to ensure a sustainable AI journey. -
Companies often encounter several challenges when implementing AI, including insufficient data quality , unclear project scopes, lack of internal expertise, and resistance to change within teams.
Security concerns and regulatory compliance can also slow down or complicate deployments.
A methodical , phased approach that includes careful planning, ongoing communication, and team empowerment is essential to overcoming these hurdles. Continuous monitoring and iterative improvements further ensure that AI initiatives remain aligned with evolving business needs. -
Ensuring the security and compliance of AI initiatives requires embedding security measures and regulatory requirements into every phase of the AI project lifecycle. This includes implementing strong data protection protocols, anonymizing sensitive information, conducting regular audits, and maintaining clear documentation of AI processes and decision-making frameworks. Compliance with standards such as GDPR, CSSF, and ISO 27001 should be integral to solution design and deployment. A proactive approach to risk management helps organizations not only meet current regulatory demands but also anticipate future ones.
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Selecting the right AI partner involves evaluating several critical criteria: proven expertise in AI technologies and frameworks, a robust security and compliance track record, an industry-specific understanding of business challenges, and the ability to offer end-to-end support — from strategic visioning to operational deployment.
Flexibility to adapt solutions to cloud, hybrid, or on-premises environments, as well as a strong commitment to continuous innovation and improvement, are also important factors.
Choosing a partner with a structured methodology and a clear focus on governance and adoption increases the chances of a successful AI transformation.