An award-winning online game developer and publisher. One of the leaders in the free-to-play MMO market, the company delivers authentic gaming experiences and services across PC, console and mobile platforms.
With over 110 million players worldwide, 15+ game titles and almost 2PB of data, Wargaming has successfully scaled AI that has driven exponential growth over the last few years. Wargaming’s data science and engineering teams have 1,500+ models running in production today that power dynamic in-game experiences, improve support efficiency and deliver advanced reporting systems that drive critical business decisions. Wargaming has successfully scaled their AI across business units by effectively identifying toxic chat for support, improving products for R&D, increasing ROI for marketing, and enhancing reporting across the organization.
With 1,500 models running in production on a single server solution, Wargaming hit their cap. They needed to scale servers, add accelerators and deploy more models but were constrained to bare metal provided with an expensive legacy platform. Because licensing was per core, the overhead cost of adding servers was extremely high and would take months to instal. Not only that, but their data scientists resisted their existing platform, because it limited them to a language and packages pre-approved by the platform. Wargaming needed a solution that could keep up with their growth. They required support of large-scale models in production, with the flexibility to scale their servers that minimized overhead costs. They wanted an easier and more cost effective way to improve performance and scale to hybrid cloud fast.
Wargaming is able to support massive amounts of models in production with fully automated pipelines across their product, support and business reporting units. Compared to their legacy platform, cnvrg.io delivered a modern Kubernetes and cloud native based infrastructure that easily blended with existing IT and offered the ability to grow without limitations. With cnvrg.io, Wargaming was able to utilize the powerful machines they already had, and easily add acceleration and powerful servers to achieve even better performance. Wargaming has achieved the same performance at half the price, transferring all 1,500 models from their legacy platform to the flexible and container based cnvrg.io. The data scientists were able to quickly adapt to cnvrg.io with an intuitive UI that gave them the flexibility to use their preferred language, add customized packages and use other open source capabilities. The data and infrastructure team has gained visibility and control to manage the budgets for projects, and seamlessly add new resources as needed.
Wargaming gained flexibility and scale that they never could with their legacy platform. cnvrg.io has enabled Wargaming to fully automate 1500 models in production while accelerating continuous application delivery. Wargaming has achieved results at the same performance in half the time and at half the cost of their legacy platform. cnvrg.io has enabled them to seamlessly adopt new servers and accelerators to improve performance. Wargaming has saved money and time by not having to purchase and install a new bare metal machine from their previous vendor. Now they can scale seamlessly to a hybrid cloud environment, add accelerators and grow to maximize performance. They have accelerated their ML pipeline by more than 50% by eliminating delays from ML platform developers. Now, data scientists can run their entire ML workflow autonomously, without DevOps or platform developers. In addition, Wargaming has achieved a nearly impossible goal, approval from the data science team. For the first time, Wargaming’s critical team of data scientists are lining up to use cnvrg.io. As hands on problem solvers, they love cnvrg.io’s open platform that enables them to customize and improve performance based on their specific use cases.
Announcing CORE, a free ML Platform for the community to help data scientists focus more on data science and less on technical complexity
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