Xsolla – AI Training for Global Engineering Teams

Project details

Empowering developers to integrate AI into real-world software development workflows.

Xsolla, a global leader in video game commerce, partnered with us to train over 100 engineers across their international teams on the latest AI tools and techniques. The objective was to improve engineering productivity, enable faster feature delivery, and encourage broader adoption of AI in their development lifecycle.

Services

  • GitHub Copilot
  • Cloude Sonnet 3.5
  • JetBrains AI
  • OpenAI (GPT-4)
  • Custom GPTs
  • Whisper (multi-modal code + audio)
  • Engineering Productivity

Challenge

Despite having a strong engineering culture, Xsolla sought to bridge the knowledge gap around AI tools like GitHub Copilot, JetBrains AI, ChatGPT, and other emerging platforms. Teams needed practical, hands-on training to move beyond experimentation and begin applying AI confidently to real codebases and workflows.

Approach

We delivered a multi-day, hands-on training program tailored to their stack and use cases. The sessions focused on enhancing developer productivity through AI-assisted coding, advanced prompting, code refactoring, and automation of time-consuming tasks. We also introduced lesser-known tools and open-source platforms that could provide long-term competitive advantages.

Outcome

Delivered a machine learning recommendation engine in 12 weeks that boosted in-app purchase conversions by 22% and cut transaction declines by 15%. The platform handled hundreds of thousands of concurrent users with <250ms response times.

What We Did​

01/Custom AI Training Curriculum

Developed a hands-on program centered around AI-assisted development, tailored to Xsolla’s languages, frameworks, and engineering needs.

02/Live Sessions Across Regions

Delivered engaging sessions with live demos, real dev scenarios, and practical workflows focused on code generation, PR reviews, and productivity.

03/Workflow Integration & Enablement

Trained engineers on how to use AI tools not just in isolation, but as part of their Git workflows, terminal sessions, and IDEs.

04/AI Strategy & Adoption Guidance

Helped engineering leads identify where AI tools could be embedded long-term and how to scale adoption effectively across teams.