Applied AI systems
We focus on turning useful AI workflows into products that can operate reliably in real environments, not only in demos.
Research
Research
We are interested in the systems research behind affordable AI: productized model workflows, decentralized infrastructure, and verifiable useful compute.
Decentralized compute
Alysis explores how distributed GPU contributors can support training and inference workloads while preserving strong incentives.
Proof of useful work
Our work examines how AI workloads can be validated and rewarded based on measurable utility rather than arbitrary computation.