Capabilities
Engineering across the full path from power to production.
Five areas of focus, each organized around a problem infrastructure owners face. Engagements can start at any layer — most begin with an honest look at where the risk is.
Infrastructure Strategy & Technical Diligence
Capital is about to be committed, and the technical risk hasn't been priced.
We assess whether a site, design, or platform can actually deliver the AI capacity it promises — power and cooling headroom, network and hardware architecture, delivery schedule, and the operational model needed to run it.
What you get
- A clear view of technical and delivery risk before you commit capital
- Prioritized findings with the questions to put to developers, OEMs, and contractors
- Readiness gaps identified early, when they are still cheap to close
Typical scope
- Site and facility readiness review
- Power, cooling, and density assumptions vs. target GPU platforms
- Network fabric and storage architecture review
- Schedule, supply-chain, and integration risk
- Operational model and staffing assumptions
GPU Infrastructure & AI Cloud
Racks are arriving. Turning them into a platform customers can use is a different job.
We translate GPU hardware, high-performance networking, storage, and orchestration into a production computing platform — one that schedules work efficiently, isolates tenants, and stays observable at scale.
What you get
- Faster path from hardware delivery to billable or productive capacity
- Clusters validated against the workloads they were bought for
- A platform your team can operate, not just one that passed bring-up
Typical scope
- GPU cluster integration and bring-up planning
- InfiniBand / Ethernet fabric design review and validation
- Kubernetes and batch scheduling for training and inference
- Multi-tenant isolation, quotas, and capacity management
- Neocloud platform engineering
Technical Delivery & Owner's Representation
Many parties are building one system, and nobody owns the seams between them.
We act on the owner's side of the table — coordinating integration across facility, network, hardware, and software scopes, defining acceptance criteria, and holding every party to a shared definition of done.
What you get
- One accountable technical view across contractors and vendors
- Acceptance criteria written before the work, not after it
- Fewer surprises at handover and a schedule grounded in real dependencies
Typical scope
- Technical owner's representation
- Integration planning across facility, IT, and platform scopes
- Vendor and contractor technical coordination
- Acceptance criteria and test plans
- Delivery risk tracking and escalation
Platform Engineering & Reliability
The system works in the demo. Production needs it to work at 3 a.m. under load.
We build resilient software platforms with automation, observability, security, and operational discipline — so AI infrastructure behaves predictably as it grows and changes.
What you get
- Infrastructure defined as code, reproducible and reviewable
- Telemetry that shows failures before customers do
- Lower operating cost through automation and right-sizing
Typical scope
- Infrastructure as code and environment automation
- Observability: metrics, logs, traces, and GPU telemetry
- Site reliability engineering and incident practice
- Security baselines, access control, and secrets handling
- Cost and capacity reviews
Commissioning & Operational Handover
Construction ends. Operations begins. The gap between them is where projects stall.
We validate end-to-end readiness — from power and cooling behavior under real load to cluster performance and runbooks — and establish the processes needed for sustainable operations.
What you get
- Evidence that the system meets its acceptance criteria end to end
- Operations teams who receive documentation, runbooks, and working tooling
- A lifecycle plan for expansion, refresh, and change
Typical scope
- Integrated systems testing at the IT and platform layers
- Burn-in and workload performance validation
- Runbooks, escalation paths, and on-call readiness
- Operational handover and knowledge transfer
- Lifecycle and expansion planning
Planning AI capacity? Talk to an engineer before you commit.
Share where your project stands — site, power, hardware, or platform — and we'll tell you plainly where the delivery risk is.