Neoclouds
Show customers how their workloads perform at production scale on your fleet.
Use workload evidence from evaluation through renewal.
During evaluation, the results support capacity selection. Once the customer is running, they support performance reviews, renewals, and expansion planning.
Presales and evaluation
Capture a prospect’s workload at a scale they can run, then simulate the production scale and identify configurations that meet their targets.
Training and inference in production
Use the same process to locate network performance problems before they become support tickets or consume additional capacity.
Renewal and expansion
Compare results across review periods to show how workload performance changed and where additional capacity can support growth.
Run the process across your customer base.
Use Scala’s API to submit traces, test a range of configurations, and return results through your existing presales, support, and operations workflows.
Capture customer workloads
Add trace capture to the customer’s PyTorch training script, then submit the trace with the network configuration you need to evaluate.
When a prospect cannot share a workload, begin with Scala’s trace library and replace it with their trace when one becomes available.
Automate analysis and deliver it under your brand
Use the same API workflow to evaluate one prospect, diagnose a support case, or run a group of renewal reviews.
Include the results in your customer materials and workflow. The customer does not need to manage a separate Scala engagement.
Start with one customer workflow.
A twenty-minute call identifies the first presales, support, or renewal workflow to evaluate with Scala.