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Our customer is an innovative organization at the forefront of AI-driven solutions. Their team comprises passionate scientists, engineers, and entrepreneurs with deep expertise in computer vision, natural language processing, and signal processing. By leveraging cutting-edge technologies and platforms, they empower businesses across industries to unlock the true potential of AI and transform their operations. Initially, our customer faced significant computational challenges in training their machine learning models efficiently. As a company focused on delivering cutting-edge solutions in computer vision, natural language processing, signal processing, and sensor-based AI platforms, they needed a robust infrastructure to support their advanced ML training requirements. The existing infrastructure lacked the necessary compute power and flexibility, hindering the development and deployment of their models.
Recognizing the critical need for a scalable and cost-effective solution, Quadra recommended hosting their ML training models on Google Cloud's Compute Engine with accelerator-optimized VMs. By leveraging Graphics Processing Units (GPUs) specifically designed for high-performance computing, our customer could unlock the full potential of their ML algorithms. The collaboration involved a detailed analysis of their workload requirements and infrastructure optimization to ensure seamless integration and performance enhancement.
With the migration of their ML training models to Google Compute Engine with GPU support, our customer witnessed a remarkable transformation in their machine learning workflows. The accelerator optimized VMs significantly reduced training times, allowing them to iterate faster and improve the accuracy of their models. The flexible pricing and customizable infrastructure of Google Cloud enabled our customer to optimize resource allocation and control costs effectively. This, in turn, translated into cost savings and a competitive edge for their business.
Multi-billion-dollar enterprise, and India’s most trusted two-wheeler manufacturer leverages public cloud to save costs and propel digital transformation