TCP-split proxies have been previously studied as an efficient mechanism to improve the rate of connections with large round trip times. These works focused on improving a single flow. In this paper, we investigate how strategically deploying TCP-split proxies in the cloud can improve the performance of geo-distributed applications entailing multiple flows interconnecting globally-distributed sources and destinations using different communication patterns, and being subject to budget limitations. We present CloudPilot, a Kubernetes-based system that measures communication parameters across different cloud regions, and uses these measurements to deploy cloud proxies in optimized locations on multiple cloud providers. To this end, we model cloud proxy acceleration and define a novel cloud-proxy placement problem. Since this problem is NP-Hard, we suggest a few efficient heuristics to solve it. Finally, we find that our cloud-proxy optimization can improve flow completion time by an average of in four different use cases.