“Our mission is to make managing data for edge AI indistinguishable from cloud environments. By eliminating data complexity, we empower developers to build reliable, trustworthy, and truly distributed intelligent systems.”
— Addo Smajic, CEO of Source
Built for Edge AI Reality
Source’s distributed data stack ensures AI models and agents run reliably on real devices—even with intermittent connectivity—while maintaining data consistency and cryptographic integrity across the entire system. Their edge-first document database, DefraDB, synchronizes peer-to-peer across sensors, servers, and everything in between, enabling conflict-free merging and trustworthy data lineage.
Solving Data Portability and Interoperability
A critical challenge in edge AI is managing data across heterogeneous devices, evolving schemas, and fragmented ecosystems. Source tackles this head-on with LensVM, their bi-directional data transformation engine that automatically handles evolving data formats. This means the same datasets can seamlessly power AI models, analytics, and operational systems—regardless of schema differences or device capabilities—without manual intervention or data loss.
This approach enables true data portability: models trained on one device can leverage data from others, federated learning workflows can span diverse hardware, and organizations can avoid vendor lock-in while maintaining complete control over their data.
Practical Benefits for Developers
This foundation enables developers to build robust on-device AI that stays responsive during outages, supports federated learning across diverse fleets, and maintains end-to-end data provenance—all with simple integration patterns and without sacrificing interoperability.
We’re proud to partner with Source as we unlock the full potential of edge AI together.