How We Build
Infrastructure is five layers deep, and most vendors sell one of them. GenesysLabs.ai designs and builds the bottom two, deploys and configures the third, builds the fourth as its own platform, and partners on the fifth.
The Stack
| Layer | What It Is | What GenesysLabs.ai Does |
|---|---|---|
| L0 — Physical Infrastructure | GPU servers, AI workstations, CPU servers, storage, networking, power and rack design, cooling, edge systems | Designed and built in-house |
| L1 — Fabric & Cluster | Compute and storage fabric, interconnect design, cluster topology, node design, rack-scale architecture | Designed and built in-house |
| L2 — Runtime & Orchestration | Kubernetes, Slurm, container runtime, GPU scheduling, workload orchestration, infrastructure automation | Deployed and configured |
| L3 — Platform (GLIDS) | Deployment standardization, benchmark validation, monitoring and observability, infrastructure lifecycle | Our own platform layer |
| L4 — Applications & Agentic AI | AI products, agent platforms, evaluation and observability tooling | Delivered with software partners |
GLIDS
GLIDS — the GLabs Intelligent Deployment System — is the layer that makes a deployment repeatable instead of bespoke. One image, one benchmark gate, one monitoring baseline, one support playbook, whether the deployment is a single workstation or a 2,000-node cluster.
GLIDS deploys every solution lane. AI Solutions are also built on the GLabs AI Stack and are deployed and validated through GLIDS.
The Four Stages
| Stage | Detail |
|---|---|
| Validate | Burn-in testing and a GenesysBench™ benchmark pass before handover — no system ships on spec-sheet numbers alone. |
| Standardize | A single GLIDS base image on every GLIDS deployment — the same baseline on one workstation or a 2,000-node cluster. |
| Integrate | Racking, cabling, network fabric and power validated on-site — or pre-cabled at the factory for POD-class systems — before go-live. |
| Support | One SLA and support playbook across the entire line, Edge AI through AI Factory. |
What GLIDS Does Today
Available now
- Standard base image on every system (Ubuntu-based, CUDA 13.2, PyTorch 2.11)
- GenesysBench™ validation pass before handover
- Standardized deployment runbooks
- Monitoring stack on HPC deployments (Grafana, Prometheus, DCGM)
In development
- Benchmark automation
- Deployment automation
- Unified observability across customer deployments
Roadmap
- Infrastructure abstraction
- GPU workload management across deployments
- RAG stack support
- Model-serving integration
Partner-delivered
- Application layer
- Agentic AI products
- AI evaluation tooling
GenesysBench™
Acceptance shouldn't mean "it powered on." GenesysBench™ is the validation pass every system clears before handover — run against the workloads the system was sized for, not a synthetic score. It's also what turns a hardware conversation into a technical one: the numbers are the customer's, measured on their configuration.
NVIDIA Ecosystem
GenesysLabs.ai builds on NVIDIA platforms across the range — Jetson at the edge, RTX PRO and H200 in workstations, H200 NVL and HGX in servers, GB200 NVL72 at AI Factory scale — and deploys and supports official NVIDIA systems including DGX Spark, DGX Station GB300 and DGX SuperPOD.
NVIDIA Studio Certified · Intel Gold Partner · AMD Arena Member
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