AI Consulting for Game Studios and Interactive Media

The opposite. At indie scale, a three-person team is the AI stack: you can't hire a 10-person QA department or a full community team. We scope to where the bottleneck actually is: usually community moderation and localization for 5-person studios, QA automation for 15-person teams, production and analytics for 50+. The goal is to keep you small and focused on creative work, not to bolt on enterprise tooling.

Studios worry, correctly, about leaking unreleased code, art, or design docs into training data. We recommend business or enterprise plans whose terms exclude your inputs from training by default (for example Claude Team or Enterprise, or ChatGPT Business or Enterprise), and your team reviews those terms before anything is uploaded. Where code or assets cannot leave your network, we scope a self-hosted option with your engineers. Every engagement starts with mapping what can touch cloud AI and what must stay on-prem.

The industry is still figuring out the line and it's moving fast. We take the position that AI should multiply designer output (quest variants from a designer's blueprint, NPC barks from a writer's voice guide, item descriptions from a template), not replace authored content. Steam has asked developers to disclose generative AI content on their store pages since 2024, and platform policies keep changing, so we build with a clear record of where AI was used, human review at each step, and editable source prompts.

Three ways. First, recruiting: job posts and dev blogs that rank on Google for "senior gameplay engineer Vancouver" reach candidates who are already looking. Second, player discovery: dev-blog content ranking for "games like [genre]" and "hidden gem indie 2026" drives wishlists. Third, AI search visibility: as players ask ChatGPT "what studios made [game]," clear, consistent studio pages give it accurate information to cite.