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Build, Run, and Manage Your
AI Factory

Maximize GPU utilization, lower cost-to-serve, and eliminate bottlenecks across training and inference — from a single platform.
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The platform

AI Factory Operations, Governed from
Silicon to Token

VEKTOR runs the full stack — fleet, fabric, workloads, tokens, tenants — and turns racked
hardware into a metered, revenue-generating service.

Manage your GPU fleet end-to-end
Provision, monitor, and optimize clusters at scale. Discover rack topology and switch fabric, track thermal and power draw per rack, and plan capacity across idle, cool, warm, and hot GPU pools.
Govern token economics and cost-to-serve
Measure live token throughput and latency by model, tenant, and workload. Compute exact cost-to-serve in real time, and benchmark private inference against public API spend to drive placement decisions.
Deliver multi-tenant AI as a service
Onboard tenants with dedicated GPU allocations, self-service API access, and RBAC. Schedule workloads by SLA, cost, and capacity — then meter per-tenant consumption for chargeback and billing.
Orchestrate and port LLM workloads freely
Route inference across vLLM, LiteLLM, TensorRT-LLM, and public APIs. Migrate models between private and public providers without re-engineering, with support for PyTorch, TensorFlow, ONNX, and CUDA.
Enforce governance, compliance, and security
Apply RBAC, SSO, and MFA with per-tenant policies. Maintain full audit logs and compliance dashboards, and secure execution with hardware-backed confidential computing.
Operate the factory with an ITOps copilot
Run everything through ChatOps with LUMI — ask about fleet health, idle GPUs, and underperforming racks; trigger runbooks, rollouts, and rollbacks through human approval.

Sovereignty & private inference

Run AI Inference
Inside Your Own Boundary

Models, data, and tokens stay within your perimeter. Meet data residency and regulatory requirements without giving up model
choice or economics.

Private LLM inference on your GPUs

Data residency & regulatory control
Hardware-backed confidential computing

Benchmark cost-to-serve, private-vs-public

Deliver & Manage AI Factory Faster
with Vektor

Read The Complete Solution Brief

Why VEKTOR

Extract Maximum ROI from Your AI Factory

Platform teams get real-time control over performance, power, and cooling. Operators get tokenomics, isolation, and portability that hold across private and public LLMs.

01

Higher fleet utilization
Real-time cost per million tokens, computed from GPU power, PUE, and interconnect — so placement decisions are made on economics, not guesswork.
02
Revenue visibility, tenant by tenant
Metered token consumption and workload-level economics make chargeback, showback, and pricing defensible.
03
Freedom from lock-in
Vendor-neutral orchestration keeps workloads portable across private and public LLMs, protecting margin as the market shifts.
04
Governance that scales with you
Per-tenant policy, audit trails, and confidential computing let you grow tenants and workloads without loosening control.
05
Faster time to production
A structured path — design, build, operate, handover — takes a factory from topology plan to client-autonomous operation.

Delivery model

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.

01

Design
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.

02

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

03

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

04

Monetize
Turn your AI factory into a revenue engine. Meter token usage per tenant, run chargeback and showback, and track revenue against cost-to-serve.

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Simplify How AI Factories Are
Deployed and Operated

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About UnityOne AI ™

UnityOne AI™ is an agentic intelligence platform for ITOps management, comprising CERNE, LUMI, and VEKTOR. CERNE replaces dozens of cloud management tools by unifying DCIM, AIOps, HCMP, FinOps, and GreenOps within a single AI-driven control plane. LUMI, the AI copilot, provides contextual intelligence, operational recommendations, and workflow automation, while VEKTOR enables enterprises to provision, orchestrate, and scale AI factories with the lowest cost-to-serve. The UnityOne AI™ suite enables enterprises to simplify hybrid/multicloud operations, strengthen governance, optimize resource utilization, and accelerate transformation to AI-driven ITOps.

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