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# ML/AI Customer Story — 30% cost savings **Industry:** ML/AI **Cloud:** AWS **Outcome:** 30% cost savings ## Summary Parallel multi-customer environment provisioning on AWS plus CloudWatch observability. No more manual setup, no more human errors. ## The Challenge Agentz was already operating on the cloud but hit a wall on manual provisioning and maintenance when spinning up environments for each new customer. The setup was labor-intensive and susceptible to human error, which directly slowed customer onboarding.As a data-intensive business with heavy compute and database requirements, Agentz needed cost-effective infrastructure and automated cloud environment provisioning — not another layer of custom scripts to maintain. ## The Solution CloudHedge implemented automation-driven infrastructure provisioning on AWS, enabling parallel deployment of services instead of sequential, hand-crafted setup. CHAI Flow-style orchestration handled the multi-customer rollout pattern end-to-end.AWS CloudWatch was wired in for comprehensive environmental monitoring, so every new environment came with observability from day one — no retrofitting, no gaps. ## The Outcome Agentz achieved 30% cost savings as infrastructure spend began to align with actual consumption instead of over-provisioned, always-on environments. Customer onboarding accelerated dramatically, because parallel service deployment replaced the old manual sequence.System performance held steady with error-free operations, and the team freed up engineering time that used to disappear into provisioning work — reinvested into the AI product itself. ## Stack - AWS - AWS CloudWatch - CHAI Flow ## Contact Book a demo: /contact/ Email: hello@cloudhedge.io