The Problem
High costs and rigid infrastructure slowed growth.
Gendo AI faced significant infrastructure challenges that hindered their ability to scale effectively. Their GPU-based architectural visualization platform required substantial computational resources, but their existing infrastructure was both costly and inefficient. They were paying for continuous hardware uptime, even when GPUs were sitting idle, leading to excessive operational expenses. This rigid pricing model meant they were constantly overpaying for resources they weren’t fully utilizing.
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Additionally, their infrastructure was unable to handle sudden spikes in user demand. When architects and designers flooded the platform with requests, system performance would degrade, causing long wait times for AI-generated visualizations. This inconsistent user experience not only frustrated customers but also limited Gendo’s ability to grow. Without a scalable and cost-effective GPU solution, they risked stalling innovation and slowing their momentum in the competitive AI-powered design industry.
The Solution
Flexible, on-demand GPUs eliminated waste and scaled effortlessly.
To overcome these challenges, Gendo AI integrated RunPod’s dynamic and flexible GPU infrastructure, allowing them to optimize both cost efficiency and performance. By leveraging RunPod’s job-based costing model, Gendo only paid for the compute power they actually used, eliminating wasteful spending on idle GPUs. This shift immediately reduced their operational costs, ensuring that every dollar spent contributed directly to processing user requests.
RunPod’s dynamic scaling capabilities also transformed Gendo’s ability to handle demand surges. Instead of relying on a fixed pool of GPUs, their system could now automatically allocate more resources during peak times and scale down during quieter periods. This flexibility meant that even during high-traffic periods, users experienced consistently fast response times. With RunPod, Gendo AI gained the agility they needed to support real-time architectural visualization without the overhead of managing and maintaining GPU hardware.
The Result
Lower costs, faster performance, and a seamless user experience.
By switching to RunPod, Gendo AI achieved substantial cost savings while delivering a smoother and more responsive user experience. Their pay-per-job model eliminated unnecessary expenses, allowing them to invest more into product innovation rather than infrastructure overhead. Instead of worrying about wasted GPU capacity, Gendo could focus on refining their AI models and expanding their platform.
With RunPod’s smart scaling, Gendo AI ensured that architects and designers could generate high-quality visualizations without delays, even during peak demand. The improved reliability and efficiency of their platform strengthened customer satisfaction and positioned Gendo as a leader in AI-driven architectural visualization. By removing infrastructure limitations, RunPod empowered Gendo AI to scale their vision—helping architects bring ideas to life faster than ever before.
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