INDUSTRIALISATION
Supporting the comprehensive integration of your most ambitious strategies
Successfully meet the challenge of scaling up
The first steps in digital transformation have been taken: companies are collecting and governing their data, exploring artificial intelligence and launching use cases. The real challenge today is industrialisation. This involves securing production, integrating data and AI into business processes, building robust and scalable cloud architectures, and meeting increased requirements for governance, cybersecurity and regulatory compliance.
Industrialise data management to make your data more reliable and valuable
Implement repositories, pipelines and quality standards that guarantee data integrity and traceability.
This approach aims to build trust, accelerate the production of AI use cases and optimise business decision-making.
Support the operational implementation of your data-driven and AI-ready transformation
Ensure continuity between strategic vision and operational execution,
with pipelines, platforms and predictive models that create measurable business impact.
Linking technology and business performance
Align cloud architecture, APIs, continuous delivery,
automation and DevOps with your business challenges to make technology a growth accelerator rather than a cost centre.
OUR EXPERTISE
From strategic framing to technical industrialisation
We support you from strategic design to operational execution of your data and AI programmes. Our teams align the technological dimension (Cloud, API, DevOps, CI/CD, web applications) with business reality to transform your use cases into concrete performance levers. This means industrialising your predictive models, automating your management tools and deploying platforms capable of generating value.
We work on both targeted audits and comprehensive transformation projects, applying four key principles: co-construction with your teams, capitalising on your achievements, knowledge transfer to ensure reversibility, and efficiency to deliver tangible results quickly. Our approach enables you to bridge the critical gap between strategy and execution, and finally reap the return on investment from your data and AI initiatives.
OUR BUSINESS CASES
Automatically structuring a technical database using AI and image recognition
A major leisure company wants to automate the collection and structuring of technical information about its products in order to optimise its business and develop new offerings.
Context
The client receives technical information from more than 50 suppliers in the form of image documents or scans, covering more than 500 products and around 20 characteristics per product. The lack of consistency between formats makes this information unusable for optimisation projects. The systematic and continuous collection of this data is crucial for developing new uses, improving operational performance and supporting decision-making. The client wanted to implement an automated, proprietary methodology capable of integrating new product information and gradually extending the scope to less priority features.
Method
We have developed an image recognition algorithm to automatically extract technical information from documents sent by suppliers. The approach was designed to consistently process heterogeneous formats and automate the continuous integration of new data. The proprietary algorithm ensures data confidentiality.
Results
The algorithm now automatically collects and structures technical information for all these products, making the data immediately usable for analysis and optimisation projects. The client has a structured, scalable database that facilitates the development of new BUSINESS CASES and continuous improvement in operational performance.
Structuring data governance in a decentralised retail organisation
Veltys supported the Chief Digital Officer in implementing governance tailored to her regionalised model in order to unlock the potential of data and AI initiatives across the business lines.
Context
The group operates under a highly decentralised model, with autonomy being part of its DNA, both at the point of sale and in regional entities.
Any data governance approach must take this complex organisation into account to ensure the alignment and transformation of data and AI uses. The challenge is to create a structured framework without stifling local initiative.
Method
We have structured governance based on accountability, with defined roles and community leadership.
Operational processes have been designed around data quality: existing documentation, interviews, IT data feedback, multi-stakeholder redesign workshops.
Actions have been focused on a concrete objective: data quality and its real impact on business lines. Structuring tools such as a project prioritisation matrix and quality monitoring dashboards were custom-designed.
Results
The quality dynamic has been launched, piloted and connected to business challenges.
Roles have been defined and integrated into a structured data programme that gives meaning and creates buy-in. Business issues have been addressed, with immediate fixes and sustainable solutions as part of the redesign and migration of data tools. The programme is grounded in reality, with concrete benefits for team performance.
Industrialising the use of data to improve the management of a fast-growing SME
Context
Veltys supported a rapidly growing French SME in its digital transformation, with the aim of industrialising the capitalisation of its knowledge and expertise. Rapid growth and an increase in project size required more precise management of activities and multiple stakeholders, anticipation of recruitment needs and accurate monitoring of potential projects. The company was aware of the potential of data to better manage its business and differentiate itself from its competitors, but many existing tools and POCs did not communicate with each other, limiting the value that could be exploited.
Method
Veltys assisted the company in improving the reliability, synchronisation and quality of existing data and associated processes. A secure and flexible cloud infrastructure was set up to centralise all available data and enable its operational use. Existing data was integrated and management tools were developed to provide a macro view of project stages, enabling more accurate monitoring and better strategic decision-making.
Results
The intervention enabled the design of tailor-made operational tools, structuring data as a strategic asset. The SME now benefits from secure and reliable data, clarified governance with rights management, and dashboards enabling effective project and resource management. This approach has consolidated the company's ability to anticipate its needs, optimise its decisions and strengthen its competitive advantage.
Designing the pricing policy for a platform-based freight service
Context
In an international transport market where prices fluctuate rapidly, a freight forwarding group decided to thoroughly modernise its tariff data management. Its ambition was to centralise all price information – buying rates, selling rates, spot rates – and automate its collection from sea and air carriers via EDI/API interfaces. This transformation aimed to offer more competitive and dynamic rates, as well as to provide operational teams with simple and powerful tools to build pricing tailored to each client, as part of the group's digitalisation strategy.
Method
Veltys mobilised its dual expertise in the sector and in technology to support the client. The teams worked with the business lines to co-build a new cloud-based data environment as a foundation for management and pricing applications. The data was integrated into a single, reliable database that is automatically updated using APIs and EDI with suppliers. Statistical models and a door-to-door recommendation algorithm were developed to improve the relevance of quotes and visualise price positioning in relation to the market. Finally, an application was designed to recommend optimised routes and facilitate operational decision-making.
Results
In just a few months, the freight forwarder has equipped itself with a centralised, cloud-based tariff data management environment. The automation of exchanges via API/EDI now makes it possible to offer dynamic and competitive rates, while data-enriched pricing tools provide teams with smarter and more tailored pricing. This transformation marks a key step in the group's digitalisation and strengthens its competitive advantage in a constantly evolving market.
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