Apolo Case Studies

PowerSetter, the largest digital energy comparison platform, transformed its services using Apolo's GPU Hub & AI-Centric Ecosystem to deliver personalized, real-time energy solutions and enhance consumer control over energy choices.
This partnership revolutionized the platform's capabilities, ensuring rapid data processing, scalability, and advanced AI-driven insights for users.

Centrobill, a leading worldwide payment processing company, enhanced its fraud detection mechanisms using Apolo's scalable, high-performance computing AI-driven solution. This partnership enabled Centrobill to process large volumes of transaction data quickly and accurately, develop advanced fraud detection models, and analyze transactions in real-time, significantly improving the accuracy and reliability of its fraud prevention efforts.

Synthesis AI revolutionized its synthetic data generation capabilities by partnering with Apolo to migrate its ML workflow from Kubeflow to Apolo Platform within their secure AWS environment. This transition enabled Synthesis AI to scale efficiently, tripling ML productivity and increasing training jobs tenfold while saving over $100,000 in computing costs.

Scott Data and Apolo have partnered to revolutionize AI computing infrastructure, integrating Apolo's AI platform with NVIDIA's DGX H100 machines. This collaboration enhances the speed and efficiency of AI deployments, providing clients with a robust system for managing AI development. The integration enables rapid provisioning of HPC resources, streamlined workflow management, and comprehensive lifecycle management of AI assets, setting a new industry standard in high-performance computing for AI.

Apolo partnered with Cato Digital to advance sustainable AI infrastructure by integrating Apolo's MLOps solution within Cato's environmentally data centers. This integration facilitates efficient AI workload growth while offering seamless access to computing infrastructure, workflow automation, and comprehensive AI/ML toolsets, all within a 100% green data center environment. The collaboration addresses the increasing demand for cloud-based AI, emphasizing energy efficiency and carbon footprint tracking, setting a new standard in sustainable AI development.

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