Pharma & life sciences
The clues to the next result are scattered across public databases, internal lab systems, and years of past experiments. We bring them together and make them askable.
// thousands of results, in systems that never met
Problems we see
- Research data spread across dozens of systems — nobody sees the whole picture, and evidence that already exists goes unread.
- The scientists who need answers cannot write the queries; the people who can write queries do not know the science.
- Internal platforms that took years to build and are quietly ignored by the labs they were built for.
- Experiments repeated because the previous result was findable in principle and not in practice.
- AI ambitions meeting GxP, data integrity requirements and IP protection — usually late.
Linked sources, and an assistant scientists can just ask
We build research data platforms that link internal results to public sources — connected data foundations — and then put a layer on top that scientists can simply ask, with every answer carrying its sources: answers on your data. Compliance is designed in from the first architecture decision rather than added once the platform works.
This is the industry where we have done our deepest work, building research data platforms at large pharmaceutical and life-science organizations.
Traceability is not a phase at the end
What that means concretely, rather than as a policy statement.
| Requirement | How it is built |
|---|---|
| Provenance | From source system to derived value, so any number on a screen can be traced back to where it came from. |
| Access control | Mirrors study and site boundaries, rather than a flat organization chart applied after the fact. |
| Change history | Survives the platform being extended, instead of resetting each time the model changes. |
| Validation | Treated as normal engineering work throughout, not a document exercise once the software is finished. |
Retrofitting any of this is what makes pharma data projects fail late, and expensively.
Working on hard scientific questions?
Let us talk about what your data could already answer.
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