From AI opportunities to industrialised solutions. Built to scale.
Weeks → days
Faster AI-assisted requirements allocation
End-to-end
From business needs and POCs to production-ready AI
At scale
AI deployed across engineering and industrial operations
Putting AI on tracks: Expleo helped a global leader in rail transport systems build and scale an AI Factory turning diverse business needs into production-ready AI solutions, improving efficiency, accelerating complex processes and enhancing the quality and accessibility of information across the organisation.
Who is the client?
Our client is a global leader in rail transport systems, designing and delivering rolling stock, signalling and integrated mobility solutions. Its complex, engineering-intensive activities involve large volumes of technical data and requirements across the project lifecycle.
What was the challenge?
The client wanted to scale the use of AI across its organisation, turning a growing range of business needs from different departments into reliable, production-ready solutions. These needs spanned complex, time-consuming activities including tender and requirements management, access to technical knowledge, test reporting and production operations.
The challenge went beyond developing individual AI tools. The client needed a scalable delivery model capable of assessing new use cases, demonstrating their value, developing and industrialising the most promising solutions, and integrating them with existing systems and processes without replacing the legacy IT landscape.
What was the Expleo solution?
Expleo established a scalable AI Factory, bringing together AI engineers, business analysts, tech leads and architecture expertise in agile squads. Working in close partnership with the client’s internal teams, Expleo teams support the full AI lifecycle from business needs assessment and POCs to custom development, integration, deployment and monitoring of production-ready solutions.
The teams combine expertise in Generative AI and LLMs, RAG and agentic architectures, machine learning and deep learning, data engineering, proprietary model building and cloud architecture. This flexible partnership model enables Expleo to address diverse use cases in parallel and adapt to evolving priorities.
How did that help?
The AI Factory has enabled our client to develop and deploy several AI solutions:
- Tender and requirements management: AI extracts, classifies and tags requirements from complex tender documents, allocates them to the relevant engineering or business teams, and feeds them into the client’s DOORS requirements management system.
- Enterprise knowledge assistant: combining RAG and Knowledge Graphs to provide employees with more accurate, contextual access to internal knowledge and project requirements through a conversational assistant.
- Automated test reporting: extracting information from heterogeneous data sources to automatically generate consistent test reports based on predefined templates.
- AI-assisted production operations: enabling shop-floor operators to report issues by voice, automatically creating structured incident records and suggesting action plans based on previous experience.
- CAD similarity search: indexing and analysing complex 3D CAD files to identify similar existing components when building BOMs, supporting the reuse of existing designs and components.
The scope of the partnership has expanded as trust and demand have grown. Launched in 2024, the AI Factory at our client’s has scaled to eight squads working in parallel, addressing an evolving pipeline of AI use cases from different parts of the organisation.
What were the results?
The AI Factory is helping our client accelerate processes, reduce manual effort and improve the quality and accessibility of information. AI-assisted requirements allocation can reduce a process that previously took experienced engineers several weeks to just a few days, while knowledge assistants make internal expertise easier to access. On the shop floor, voice-based input makes it easier for operators to report issues directly, without having to type information into an application, while helping capture and reuse lessons learned.
The AI Factory provides a repeatable framework for leveraging AI opportunities. New ideas can be rapidly assessed through POCs, then industrialised when their value and feasibility are demonstrated. Once deployed, solutions are monitored for usage, performance, user feedback and operating costs, including LLM token and resource consumption, providing the foundations to track value and continuously optimize solutions.
Could it work for me?
Yes. The AI Factory model is particularly relevant for organisations managing complex engineering or industrial processes, large and scattered knowledge bases, heavy document management processes and significant volumes of technical data. This AI factory model gives organizations a scalable and flexible AI capability, able to respond to evolving priorities while maintaining a strong focus on adoption, cost control and return on investment.
Signalling
We deliver specialised signalling covering all V-model activities, while working with both signalling manufacturers and operators.
Product engineering
From the final design of complex systems to certifications delivered on time and within budget, we make sure products perform as expected in the hands of end users, and we apply AI to streamline the development process.
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