1 rack to 1 wing · independent · NVIDIA / Intel / AMD
Ai infrastructure
that actually ships.
Embedica designs, procures, and deploys right-sized AI infrastructure — a single GPU server to a few racks — for teams too small for the gigawatt-scale AI clouds and too complex for a plain hardware reseller. Vendor-agnostic advice, hardware that’s actually in stock, and lead times and total cost fixed before you commit.
IntelXeon, Gaudi, oneAPI
AMDEPYC, Instinct, ROCm
Who we’re built for
Built for everyone below gigawatt scale.
The AI cloud giants are built for frontier labs signing multi-year, gigawatt-scale power deals. That leaves almost everyone else — the mid-market enterprise standing up its first inference cluster, the research group scaling a pilot, the regional buyer who needs infrastructure to stay on their own soil — without a partner sized for them. That’s who we build for.
Deployment size
1 GPU server to a few racks — the range most infrastructure partners consider too small to prioritize.
Who it’s for
Mid-market enterprise, research teams, and regional or sovereign buyers who need real infrastructure, not a hyperscale sales cycle.
How we’re different
No minimum commitment and no single-vendor lock-in — a fixed-fee assessment before any hardware gets specified.
Where the market is headed
Power and cooling are the new bottleneck — not the chip
Typical AI rack power density in a few hardware generations — liquid cooling has gone from optional to default.
Site power availability, not GPU allocation, is increasingly what decides where AI infrastructure gets built.
Regional AI infrastructure and edge inference are growing alongside centralized training — most enterprises will need both.
What we deliver
Four services — no sub-menu of thirty things nobody clicks into.
Design & consultation
Workload-first sizing across GPU, CPU, network, and power/cooling — vendor-agnostic, tied to your budget and timeline.
Procurement & build
Sourcing, installation, and integration — from a single GPU server to a full-facility AI factory build-out.
AI software & platforms
NVIDIA AI Enterprise, CUDA, Intel oneAPI, AMD ROCm — deployed and integrated so hardware turns into working AI.
Support & optimization
Ongoing tuning, monitoring, and lifecycle support — a retainer, not a one-time install.
How an engagement runs
Four stages, start to steady-state.
Workload & budget
A paid assessment fixes the workload profile, power envelope, and realistic budget before any hardware is specified.
Architecture
Compute, fabric, storage, and power/cooling specified against three vendor platforms, not one catalog.
Build & integrate
Procurement, installation, and software stack integration, tracked against the lead times quoted up front.
Support retainer
Monitoring and performance tuning after go-live, backed by direct manufacturer and partner relationships.
Start here
Infrastructure readiness assessment
The fixed-fee first step, for teams who need a real number before they go to procurement or the board.
- Workload profiling across your current and planned training/inference jobs
- A vendor-agnostic build spec — GPU, network, storage, power & cooling
- Two sized options with hardware lead times and total landed cost
- A written report you can take straight into procurement
Fixed fee
Credited in full against any build or deployment engagement that follows.
Recent builds
The scale we’re built for — swap in your own deployments and figures.
