The Operating System
for Your AI Factory

Accelerate AI Factory delivery with complete control over GPU infrastructure, token throughput, workload orchestration, governance, and tenant operations – all with VEKTOR.

Get started >Get started >

The AI Factory Engine

Run Your GPU Fleet. Govern Your Tokens.
Deliver AI at Scale

Gain real-time visibility into GPU utilization, token throughput, hybrid LLM spend, and cost-to-serve – all while delivering AI services securely, efficiently, and at scale.

Full Stack GPU Fleet Management & Observability

Provision, monitor, and optimize GPU clusters at scale. Manage fleet, fabric, thermal, power, capacity, fleet topology, and inventory from one console.

Discover and visualize rack topology, switch fabric, and GPU node inventory
Monitor GPU utilization, thermal state, and power draw (kW per rack) in real time
Plan capacity across idle, cool, warm, and hot GPU pools to maximize fleet efficiency

Manage Token Economics & Cost-to-Serve

Track token usage across every workload and LLM API. Know your exact cost-to-serve per million tokens – private and public.

Measure live token throughput and latency per model, tenant, and workload
Compute cost-to-serve in real time by GPU power + PUE, and NVLink/WAN costs
Benchmark private inference economics against public API spend to drive workload placement decisions

Multi-Tenancy & Workload Delivery

Multi-tenant GPU environments with full isolation, self-service portals, intelligent workload scheduling, and workload-level token economics.

Onboard tenants with dedicated GPU allocations, self-service API access, and RBAC
Schedule AI workloads across GPU pools based on SLA, cost-to-serve, and available capacity
Get per-tenant token consumption, cost, and workload-level economics via metered dashboards

Seamless LLM Orchestration & Portability

Orchestrate workloads across LLM APIs. Migrate models between providers – keeping your AI factory flexible and cost-efficient.

Route inference requests across vLLM, LiteLLM, TensorRT-LLM, and public APIs
Migrate workloads between private and public LLMs without re-engineering
Support PyTorch, TensorFlow, ONNX, and CUDA across distributed, multi-cluster AI infrastructure

Compliance, Governance & Security

Set approval levels, role-based access, and apply per-tenant policies for safe execution. Ensure trusted and secure workloads using hardware-backed confidential computing.

Enforce RBAC, SSO, and MFA with per-tenant access policies
Maintain full audit logs, compliance dashboards, and exportable configs
Secure workload execution with hardware-backed confidential computing

Manage AI Factory with ITOps Copilot

Operate your AI factory with ChatOps. Simply prompt, orchestrate, and control everything from infrastructure to workloads with LUMI.

Ask Lumi about fleet health, underperforming racks, idle GPUs, and optimization
Trigger runbooks, rollbacks, rollouts, and workload actions through human approvals
Lumi sees the full operator/tenant workspace, executing policy-driven actions

Built for Every Stage of AI Factory Delivery

Scale from Infrastructure to Production-Ready AI

VEKTOR structures AI factory operations across four delivery stages, enabling operators to hand over a production-ready AI factory with complete client autonomy post-delivery.

Design Phase

Plan your GPU fleet topology, define tenant architecture, configure switch fabric, and establish your service catalog and token pricing model before a single workload runs.

Build Phase

Deploy and configure the full infrastructure stack. Onboard tenants, activate workload pipelines, connect public and private LLM APIs, and validate token flows.

Operate Phase

Run your AI factory in production. Monitor GPU health, manage token throughput, track revenue, optimize workloads, and enforce governance at scale

Handover Phase

Deliver a production-ready AI factory to client teams with full documentation, training, audit trails, and self-service capabilities so they gain complete operational autonomy.

Use Cases

One Platform. Three Powerful Use Cases.

VEKTOR structures AI factory operations across four delivery stages, enabling operators to hand over a production-ready AI factory with complete client autonomy post-delivery.

GPU Cloud Providers

GPUaaS at Enterprise Scale

Manage your fleet, onboard tenants, set pricing, track revenue, and deliver SLA-backed GPU compute as a commercial service from a single operator console.

Enterprise AI Teams

Private AI Factory Operations

Bring commercial-grade operational rigor to internal AI factories. Full tokenomics, workload governance, and hybrid LLM spend management across business units.

Integrators & MSPs

Production AI Factory Delivery

Build, manage, and handover production-ready AI factories – with complete audit trails, self-service tooling, and support hooks baked in from day one.

Benefits

Manage, Govern & Optimize AI Factories

Orchestrate the future of enterprise intelligence with governed AI factory operations. Purpose-built to manage, govern, and optimize AI factories, VEKTOR enables organizations to deploy private AI stacks quickly, accurately, and at lower cost.