A European AI Infrastructure Company, Built on a Decade of Delivery
GenesysLabs.ai designs, builds and deploys AI and HPC infrastructure for European organizations — from GPU workstations to sovereign AI Factories. The company is Vienna-based, and the team has been building infrastructure for around ten years.
How We Got Here
The team started in conventional IT systems and smaller infrastructure projects. Over roughly the last six years the work moved decisively upmarket — into large server deployments, HPC, AI infrastructure and data-centre-scale projects. GenesysLabs.ai is that experience brought into Europe, with a sharper focus: AI and HPC infrastructure, sovereign AI, AI Factories, and the services around them.
Leadership
CAIO & Strategic Head
Jecko Augustine
AI and technical strategy, AI architecture, solution design, and the translation of customer workloads into infrastructure requirements.
CTO & Co-Founder
Arshad Ali
Infrastructure architecture, GPU, cluster, fabric and storage design, AI Factory engineering, deployment standards and delivery quality.
CCO, GTM & Commercial Lead
Joice Augustine
Commercial strategy, customer and partner relationships, proposals, and Austrian and EU market development.
Certifications
NVIDIA Studio Certified · Intel Gold Partner · AMD Arena Member
How We Ship — GLIDS
Systems deployed for AI workloads are built on the GLabs AI Stack and deployed and validated through GLIDS — the GLabs Intelligent Deployment System. Every other deployment ships under GLIDS alone. GLIDS is not something sold separately: it's the standard every system is delivered under, Pro Grade or GLabs Enterprise, before it reaches your floor. The four stages below are how GLIDS deploys.
| 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. |
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