The work, and what it was worth

The situation

A cybersecurity platform was running GPU clusters around the clock to serve workloads that were, in practice, bursty. They were paying peak prices for capacity that sat idle most of the day, and every infrastructure change took hours to roll out.

What we did

The result

Infrastructure cost fell by 90% and full cluster rebuilds dropped from hours to under 30 seconds — meaning the team could change infrastructure during the working day instead of scheduling weekend maintenance windows.

The situation

A healthcare SaaS provider needed diagnostics to work across more than twelve institutional sites, each with its own data-protection obligations. Duplicating infrastructure per site was expensive and slow to change.

What we did

The result

Operating efficiency improved by roughly 50% across the estate, and new institutions could be brought online without standing up a parallel stack each time.

The situation

Manual and slow product classification was creating delays across a supply chain handling tens of millions of items daily. Every millisecond of latency multiplied into hours of downstream delay.

What we did

The result

The engine now classifies in under a millisecond at the 99th percentile while handling more than 50 million requests a day, removing a manual bottleneck from the supply chain.