AI for Academia
Research infrastructure that stands behind the paper
We build AI infrastructure for academic research groups — HPC clusters, training pipelines, reproducibility environments, and tooling for code sharing with industry sponsors. Our approach: the infrastructure should disappear from the researcher's path, not become the project itself.
What this covers
- HPC clusters with schedulers, monitoring, and fair sharing
- Reproducibility-first — every experiment captured with its full environment
- Bridges to industry research partners for IP transfer
- Ongoing support through the academic calendar, not just at setup