Three Business Lines, One GPU Estate They Can Govern
CLIENT PROFILE
The client is a global bank running fraud detection, a relationship-manager copilot, and risk-model training on the same private GPU estate, spanning two sites plus disaster recovery. Financial services sits among the highest AI adopters, with most large institutions already running AI in production — the stage at which the binding constraint stops being access to GPUs and becomes governance: who may use capacity, under which policy, at what cost, with what audit trail.
CLIENT CHALLENGE
Capacity was there. Control was not. Fraud scoring, the copilot, and risk modelling all competed for the same estate, and the friction was operational rather than technical:
Training crowded out inference. Long risk-model training runs competed with fraud scoring that had a latency commitment attached.
Capacity was requested by ticket. Allocation was manual, slow, and impossible to reconcile against entitlements.
No cost attribution. Finance saw one infrastructure bill and could not tell which line of business or model drove it.
Audit questions were hard to answer. Who accessed which model, under what policy, was assembled by hand from several tools.
As the bank’s Head of AI Platform Engineering put it: “We did not have a capacity problem. We had an allocation problem, and we could not prove to the regulator or the CFO who was using what.”
UNITEDLAYER SOLUTION
Rather than buy more GPUs to end the contention, the bank deployed UPC Vektor as the control plane over its existing estate — placement by policy, tenancy by business line, and cost visible per model:
1. Orchestrate
GPU pools inventoried centrally, with workload-aware placement keeping latency-bound fraud scoring clear of long training runs.
2. Govern
Tenant onboarding per business line, RBAC and SSO, entitlement-based GPU allocation, and audit logging the risk function can inspect directly.
3. Measure
GPU consumption, token throughput, and inference volume attributed per tenant and model, driving chargeback to each line of business.
4. Operate
Idle-capacity identification, guided remediation, and runbook execution, so platform engineers stop investigating layer by layer.
BUSINESS BENEFITS
Replaced manual-ticket allocation with entitlement-based self-service cutting a days-long process down to policy-governed, on-demand access.
Protected latency-bound fraud inference from training contention hrough SLA-aware placement, ending the degradation risk-model runs had been causing.
Turned one unallocated infrastructure bill into monthly chargeback per business line and per model, with a central audit trail across tenants, access, and workloads.
ABOUT UNITEDLAYER
UnitedLayer is a global provider of private and hybrid cloud solutions (single and multi-tenant), managed hosting, and 100+ PaaS. Founded in 2001, the company specializes in high-availability infrastructure designed for mission-critical enterprise and AI workloads.
