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AUDATA

A megawatt-scale NVIDIA deployment at the core

The AUDATA platform is built on dedicated capacity for enterprise AI workloads — not shared infrastructure with a queue.

The disciplines

Premier Cluster Design

A high-density AI data center environment where power, cooling, networking, and operations are designed as one system.

01

Power

Megawatt-scale capacity engineered for the sustained draw of dense accelerator racks — provisioned for the workload you run, not the average you hope for.

10MW+Deployment scale
02

Cooling

Liquid cooling designed for high-density AI racks, keeping the latest NVIDIA generations at full sustained performance.

LiquidDirect-to-chip
03

Networking

High-bandwidth, low-latency fabric built for distributed training — topology-aware and engineered at cluster scale.

FabricCluster-scale
04

Operations

Maintenance, monitoring, and lifecycle management run as an operations discipline, so delivered capacity stays delivered.

24/7Monitored
Managed platform

An integrated managed inference and training platform

One platform to fine-tune, deploy, and route between models — operated by AUDATA on dedicated hardware. Join the waitlist.

Fine-tuning

One-click fine-tuning

Enterprise clients can fine-tune models with one click — no infrastructure work, no pipeline glue.
Routing

Intelligent model routing

Route requests between frontier models and your fine-tuned models, automatically and per workload.
Training

Training for smaller labs

A one-click training platform for smaller labs and licensed model developers.
Reference architecture

Built on NVIDIA reference architecture

Deployment follows NVIDIA's reference designs for accelerated data centers — from rack topology to the software tooling stack.

Procurement

Hardware procurement, engineering, integration and deployment expertise.

Software

The NVIDIA software tooling stack, deployed and maintained as part of the platform.

Ecosystem

Commercial ecosystem alignment across the accelerated-computing supply chain.

Run your workloads on capacity that's yours.

Tell us about your training and inference roadmap and we'll design the deployment around it.