Download our brochure: harmonised data, trusted AI

Ask your AI about a compound and get one answer, not three. Your platform makes data findable and accessible. We give each core concept one definition, used in every system, so your AI gives one answer per question, traceable to your data.

Our nine-page life-sciences overview sets out the cost of waiting, a roadmap that starts small, the six services with a page for each, and how to take the first step.

What is inside

Page one shows the cost of waiting. A compound, an assay or a patient cohort means something slightly different in your lab notebook, your registration system and your clinical data. Your scientists reconcile it by hand, every integration adds a local definition, and every AI pilot inherits all of them. The longer it waits, the more it costs to untangle.

It then lays out a roadmap that starts small and scales what pays off:

1. Assess one domain in four to six weeks, at a fixed price; we credit the fee against step 2.
2. Prove it in about three months, with a working Proof of Value on your real data: model, mappings, graph.
3. Ground your AI in the proven graph, so its answers trace to source and definition.
4. Scale domain by domain over six to twelve months, adding governance, lineage, catalogues and more modelling.

Page two brings the six services together: the Assessment is the way in, four services build the shared meaning, and grounding your AI in it is the payoff. It gives the proof behind them, our mapping work for the EU Publications Office: more than 1,500 source fields mapped to one ontology, 18 schema versions followed, more than 40 document types, and the mapped data published daily.

Pages three to eight give each service its own page: the problem, what we do, what you get, where we have done it, and who it is best for.

• FAIR Interoperability Assessment: find where meaning conflicts, in four to six weeks. We trace one domain across your systems and deliver a Decision Package: the gaps that block integration and AI, a prioritised roadmap and a Proof of Value outline.
• Ontology and Vocabulary Engineering: one authoritative definition per concept. We reuse public ontologies and extend them only where their coverage falls short, as we did for the eProcurement Ontology of the EU Publications Office.
• Data Harmonisation, Mapping and FAIRification: map once, validate always, reuse everywhere. We write declarative, versioned and tested mappings, managed in our open-source Mapping Workbench.
• R&D Knowledge Graphs: ask questions across silos. We start with a thin slice of graph your scientists can query, then add sources and use cases step by step.
• FAIR Metadata Catalogues and Data Publishing: data that can be found, shared and reused. We build on open standards such as DCAT-AP, as we did for DCAT-AP-LU, Luxembourg’s national metadata profile.
• Semantic Grounding for AI: answers you can trace and audit. We connect your AI to your ontology, knowledge graph and metadata, in a confidential computing environment where data is sensitive.

Page nine is your next step: meet us in person, book the free 30-minute One-Term Challenge, or commission the Assessment. Why us: our semantic infrastructure publishes around 800,000 EU procurement notices a year as linked data for the EU Publications Office.

Who it is for

R&D data leaders who need one definition for each core entity, questions answered across data silos, and a FAIR roadmap backed by evidence. IT and data platform teams who want their systems to stay in place, mappings reviewed and tested like code, and open standards usable in any compliant tool.

Talk it through with us

The brochure is the summary; the useful part is the conversation that follows it. Take the One-Term Challenge: bring one term that means two things in your systems, and we define it once with you, live.