Your challenges
Research & Innovation: turning your data into faster, more impactful decisions
In both industry and healthcare, your teams generate and handle growing volumes of technical and scientific data.
DV DIGITAL’s Research & Innovation approach helps you structure, analyze, and leverage this data asset to transform information into faster and more reliable decisions.
Scattered data, value that is difficult to mobilize
In an engineering office, an R&D department, or a laboratory, data is not lacking: CAD models, sensor measurements, test results, medical images, analysis reports…
The challenge, for both a laboratory director and an R&D manager, is to connect this information, make it comparable, and use it to support faster and auditable decisions.
You are probably facing at least one of these operational challenges:
- Key data locked in a silo, a proprietary format, or an “informal” sharing process.
- Manual re-entry and inconsistencies between reference systems (CAD/PLM/ERP, study databases, files).
- Difficulty tracking a protocol, dataset, or model (who, what, when, why).
- AI or simulation POCs struggling to move into production due to lack of integration.
The result: longer innovation cycles, duplicated work, and limited knowledge capitalization.
A structured vision: the DICS pyramid applied to your data
At DV DIGITAL, we structure our Research & Innovation approach around the DICS pyramid: Data, Information, Knowledge, and Know-how (decide, deploy, measure). This framework helps clarify where you stand and which levers to activate to move forward.
- Data: raw facts from CAD, IIoT sensors, industrial equipment, or biomedical acquisitions (MRI, signals).
- Information: enriched and contextualized data through your PLM systems (Teamcenter), ERP, ECM, or management environments.
- Knowledge: structuring, ontologies/graphs, learning and analysis using solutions such as SWO360 and domain-specific models.
- Know-how: operational use within your workflows, decisions, AI tools, simulation environments, and quality processes.
The better the transition between these levels is mastered, the more your projects gain in clarity, reproducibility, and impact.
Our support
How DV DIGITAL supports your research and data innovation projects
Our role is to transform your scattered data into concrete operational capabilities in a progressive and secure way. We support you end-to-end, from defining challenges and use cases to structuring data and its governance, all the way to industrializing solutions through pipelines, workflows, and MLOps practices, while supporting adoption and knowledge transfer.
Data and domain expertise serving your teams
Proven technology building blocks
Continuous support approach
We combine a deep understanding of industrial environments (CAD, PLM, digital twins, ERP, data) and biomedical research contexts with strong data expertise: data models, ontologies, domain vocabulary standardization, governance, and data quality.
This dual expertise allows us to work equally well with a manufacturing engineer or a physician-researcher, translating their needs into structured models, dashboards, or concrete AI use cases.
Our research work relies on technological building blocks that have already proven their value in real-world environments:
- SWO360: structure, reconcile, and visualize your data (including SWO Manufacturing Indicators (MI) for IIoT flows and SWO Artificial Intelligence (AI) to connect Data Science tools such as Python, R, and Jupyter).
- SWOMed: structuring and leveraging multidimensional biomedical data, derived from advanced research projects.
- PLM & CAD integration: expertise in the Siemens suite (Teamcenter, NX-CAD, NX Mechatronic Design) for product lifecycle management and digital twin creation.
- Business data models: “QuickWin” models for rapid deployments and “Manufacturing” models to align bills of materials (eBOM, mBOM, cadBOM).
These components form a modular foundation: we can start with a targeted use case and then progressively extend the scope as your organization evolves.
Our approach is iterative: scoping, business workshops, co-design, useful prototypes, then production deployment and knowledge transfer to ensure successful adoption.
Sectors
Areas of excellence: industry and healthcare
Our research and innovation projects focus on two domains where data quality and traceability are strategic: industry and healthcare.
Industry: toward more sustainable and resilient operations (Industry 4.0/5.0)
We support engineering departments and technical management teams in leveraging their data to improve performance and operational control. Our work includes integrating AI into engineering processes (PLM, CAD), developing connected digital twins, and supporting energy efficiency and eco-design initiatives.
Our projects range from digital twins of assembly machines connected to real data for monitoring and optimization, to frugal innovation approaches for SMEs combining non-intrusive sensors and energy management.
Healthcare: leveraging the richness of biomedical data
We support research teams and healthcare organizations in leveraging complex health data (neuroimaging, signals, clinical data). From data structuring to Data Science and Deep Learning, we design reliable and reproducible pipelines to support research, facilitate collaboration, and accelerate the transition to operational use.
Funding and deployment
Funding and long-term sustainability of your innovation projects
Data innovation projects often include an exploratory component that is sensitive to budget constraints. DV DIGITAL leverages its internal work eligible for the Research Tax Credit (CIR – Crédit d’Impôt Recherche) to reduce the cost of the most innovative aspects.
We also support you with public funding programs (ANR, Bpifrance, Auvergne-Rhône-Alpes Region):
- Project structuring (objectives, milestones, deliverables, risks)
- Support in preparing the application and coordinating the project
- Alignment between scientific requirements, regulatory constraints, and industrialization
CONTACT
From vision to action: what would you like to explore next?
Whether you are a laboratory director, R&D manager, innovation project leader, or data manager, you probably already have a concrete starting point: a digital twin to enrich, an image database to analyze, test data to consolidate, or a predictive model to strengthen.
Our role is to help you transform these ideas into an operational trajectory: defining the challenges, identifying relevant datasets, selecting the right technological building blocks, developing initial demonstrator use cases, and then progressively expanding the scope.