Case Study
AIthena: The Data Foundation
FAIR data fabric powering the entire agentic ecosystem
Building the data infrastructure that makes enterprise AI actually work. Without clean, accessible, well-governed data, even the most sophisticated AI is useless. AIthena solved the foundation problem.
!The Data Chaos
Clinical trial data was scattered across dozens of systems, locked in silos, and formatted inconsistently. Scientists spent 80% of their time finding and cleaning data, only 20% actually analyzing it.
- Data scattered across disconnected systems and formats
- No unified way to query patient cohorts across studies
- Compliance and governance requirements slowing access
- AI tools couldn't access the data they needed to be useful
FAIR Data Fabric
AIthena implements FAIR principles (Findable, Accessible, Interoperable, Reusable) as infrastructure. Every dataset becomes a product with clear ownership, quality metrics, and API access.
- Unified patient cohort queries across 50+ clinical studies
- Real-time sync with source systems, sub-second query response
- Standard data models (CDISC) enabling cross-study analysis
- API-first architecture ready for AI agent consumption
Architecture
AIthena uses a data mesh architecture where each domain owns its data products, with a central fabric providing discovery, governance, and access control.
Timeline
Key Lessons
Data infrastructure is the unglamorous foundation that makes AI actually work
FAIR principles sound abstract until you try to build AI on messy data
Data-as-product thinking transforms how teams share and consume data
The best AI system is worthless without accessible, clean data behind it