Intelligent Infrastructure management for next‑gen AI workloads

Maximize your GPU usage. Reduce your OpEx.

Run your on-demand, ad-hoc fine-tuning/inferencing/agentic workloads on Vecta's shared GPUs infra for a fraction of the usual cost — or deploy the same orchestration layer on your own cluster to maximize GPU utilization and reduce OpEx.

# Run serverless fine-tuning vectacli job submit \ --gpu a100:0.25 \ --data s3://dataset \ --train train.py # Orchestrate your own cluster vectacli cluster attach \ --provider k8s \ --optimize utilization

Serverless Fine‑Tuning & Inference

Submit training or inference jobs on demand with hard multi‑tenancy. Vecta Compute multiplexes workloads across shared GPUs with automatic scaling and per-minute usage billing.

Deploy on Your GPU Cluster (Enterprise/Service Providers)

Install the Vecta Compute orchestration layer on‑prem or in VPC with complete security and hard multi‑tenancy. Increase GPU utilization, enable multi‑tenant scheduling, and reduce infrastructure OpEx.

GPU Orchestration, Re‑engineered

Fractional GPUs

Slice GPUs into secure fractions with QoS isolation.

Multi‑Tenant Scheduling

Preemptive, priority‑aware placement across workloads with enterprise-grade hard multi-tenancy.

Utilization Optimization

Advanced engineering optimizations like VRAM defragmenter maximize GPU usage across workload cycles, with zero idle GPU times.

Advanced Features

First to tackle Carbon‑scheduling of jobs to reduce runtime energy costs on a global scale.

We Believe

You never pay for idle GPU time — only for what you actually use, by the minute.
No tax for glossy dashboards or bloated pipelines that don’t accelerate your workloads.
No lock‑in. No multi‑year GPU contracts.
Your team’s focus stays on the science and the algos — not infrastructure firefighting.
AI infrastructure should cost less every year. We make that happen.