AI for Manufacturing Industry: Boost your industrial performance with Augmented Engineering

Leverage industrial and physical AI for robust, explicit, and field-executable production decisions

Industry is entering a new era. Following the foundations of Industry 4.0, which focused on data collection and visualization, Industry 5.0 places people, sustainability, and resilience at the heart of industrial transformation.

Industrial AI and agent-based systems enable organizations to move from simple passive monitoring to augmented decision-making, transforming industrial data into actionable intelligence. This enables faster, safer, and more efficient decisions, thereby improving OEE (Overall Equipment Effectiveness), stabilizing quality, and reducing energy consumption, waste, and operational costs.

Through a modular and scalable approach, ALTEN provides real-time, explainable, and directly actionable recommendations, ensuring that operators remain in control while leveraging the insights and assistance provided by AI.

Our AI for Manufacturing offering: from scoping to industrialization

• OT/IT, LLM, and MLOps: Secure Deployment and Scalable Industrial AI Solutions
• Process & Physical AI: Decisions grounded in real-world industrial processes and safety constraints
• Data, Machine Learning & Vision: Early detection and proactive adjustments
• Agentic & Generative AI: Contextual assistance and best-practice sharing for operators

Business Framing & Value Definition

This phase aims to align objectives and priorities, map out data and constraints, and then prioritize 2 to 3 high-impact use cases to create a pragmatic roadmap.

Solution Design & Business Case

This second step involves selecting AI technologies (physical, generative, agent-based, machine learning, computer vision, etc.), as well as the deployment architecture (Edge Cloud), designing the operational use case, and building a business case that guarantees ROI.

Pilot in Real Conditions

Here, the goal is to demonstrate the impact on a priority asset, measure the gains, validate robustness and explainability, gather field feedback, and then decide on scaling.

Industrialization & integration

Industrialization and integration involve packaging the solution, then deploying it into production alongside OT/IT systems, organizing its operation and monitoring, and finally, preparing a multi-site deployment kit.

Adoption, Run & Scale

Finally, this last stage includes training teams, operating and monitoring the solution with continuous improvement, integrating performance routines, and deploying the solution across all sites.

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