01
Research fragmentation
Scientific data, literature, and trial knowledge are spread across isolated repositories and teams.
Research, Regulatory, and Commercial AI at Scale
Unify trial data, scientific literature, safety signals, and commercial context so teams can move faster with traceable answers.
The Challenge
02
Regulatory pressure
Every claim and workflow needs lineage that can stand up to audit and review.
03
Slow cross-functional insight
R&D, medical, safety, and commercial teams rarely operate from one contextual model.
Industry visual
What You Can Build
01
Use case 01
Scientific knowledge graph
Connect studies, targets, and evidence
Create a shared graph across publications, compounds, pathways, and internal findings to accelerate discovery and reuse insight.
2x faster discoveryBetter knowledge reuse
02
Use case 02
Clinical trial intelligence
Query protocol and site context
Link protocol changes, patient cohorts, sites, vendors, and outcomes for faster operational and scientific decisions.
Clearer trial contextLess manual stitching
03
Use case 03
Safety & signal management
Surface related evidence
Connect reports, literature, patient context, and historical decisions to help teams investigate safety signals with better traceability.
Richer evidence trailsMore confident review
04
Use case 04
Medical and commercial Q&A
Answer with grounded evidence
Support internal teams with assistants that retrieve approved, role-appropriate answers backed by trusted sources.
90%+ traceable coverageSafer AI for knowledge work
Live workflow
Scientific knowledge graph
Target-pathway relationships
Study evidence graph
Publication-to-claim lineage
"
What changed for us wasn’t just speed — it was being able to move faster without losing scientific and regulatory confidence.
Knowledge strategy lead, global life sciences company
How It Works
01
Connect
Bring in core systems, event streams, and files without forcing teams into a new stack.
02
Unify
Model relationships automatically so teams can trace how entities connect across systems.
03
Deploy
Power copilots, analyst workflows, and governed AI on top of trusted graph context.
Works alongside VeevaWorks alongside MedidataWorks alongside SnowflakeWorks alongside Databricks
Customer Story
Customer story
A life sciences team unified scientific and operational knowledge into one graph
Researchers, medical teams, and operations leaders now work from a shared evidence layer that improves discovery, review, and cross-functional decision-making.
Faster insight reuse
Traceable answers
Cross-team shared context
See How Life Sciences Teams Use Fluree
Connect scientific, clinical, and commercial knowledge into one trusted graph built for high-stakes AI workflows.
Explore pharma use cases