Solution brief
Research & Education
Give faculty and students fair access to modern AI hardware. OWS supports shared partitions, quota policies, and grant-friendly billing so research moves faster.
What we deliver
- Shared partitions — Scheduler policies for fairness across groups; burst pools for paper deadlines.
- Onboarding — Templates for common research frameworks and course-sized allocations.
- Collaboration — Project spaces, shared storage patterns, and integration with campus identity where applicable.
- Sustainability — Right-size jobs and use batch tiers to reduce idle energy and cost.
Typical engagement
- 1Discovery — workload profile, SLOs, data residency, and budget.
- 2Architecture — cluster topology, APIs, and integration points.
- 3Pilot — limited production or benchmark phase with clear exit criteria.
- 4Scale — hardening, FinOps, and continuous optimization.
Architecture & security
Designs are adapted per customer: VPC-style isolation, encryption in transit and at rest, secrets management, and least-privilege access to control planes. We document data flows for security review and support private connectivity options where required.
Success metrics
We align on measurable outcomes — training throughput (tokens or samples per dollar), inference p99 latency, cost per 1M tokens, job completion rates, and uptime against agreed SLOs. Dashboards and monthly reviews keep both teams honest.
Related products
This solution composes OWS products. Your team can start from any layer and expand.