HEXBIT
Contact Sales

Create Training Job

This guide introduces create training job on HEXBIT AI Cloud and the decisions to confirm before production use.

i

Product availability and exact configuration are confirmed with the HEXBIT team for each project.

Overview

HEXBIT provides a consistent path for planning compute, storage, networking, and model services around an AI workload. Begin with the operating outcome, then select the delivery model that fits performance and governance requirements.

Core concepts

Workload

The model, data, runtime, and target performance.

Capacity

The compute, storage, and network resources reserved for the work.

Before you begin

  1. Describe the workload and expected traffic or training scale.
  2. Identify data location, security, and access requirements.
  3. Define the target timeline and capacity model.

Configuration example

project: example-ai-workload
runtime: accelerated
capacity: confirmed-per-project
network: private
storage: persistent

Next steps

Review the workload with our architecture team to confirm a practical deployment path.

Contact HEXBIT