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Gaming TechnologyCase Study

Interverse.ai - Private Gaming AI System

Client

Interverse.ai

Duration

6 months

Team Size

5 developers, 3 AI specialists, 2 game designers

Interverse.ai Private Gaming AI

Problem Statement

Interverse.ai needed AI that could create dynamic, adaptive game worlds while ensuring player data and gaming patterns remained completely private and never shared with external services.

Private NPC Behavior System

Executive Summary

Interverse.ai approached us with an ambitious vision: to create the world's first truly adaptive gaming universe where every player interaction shapes the game world in real-time. As a cutting-edge gaming company with over 2 million daily active users, they were facing a critical challenge that many game developers encounter—how to create dynamic, engaging content that responds to player behavior without compromising user privacy or sharing sensitive gaming data with external services.

The gaming industry has always been about creating immersive experiences, but traditional game development relies on pre-scripted content and static NPCs. Interverse.ai wanted to break this mold by creating AI-powered NPCs that could learn from every player interaction, adapt their behavior based on individual player preferences, and create truly dynamic game worlds that evolved with their community. However, they needed to achieve this while ensuring that player data, gaming patterns, and personal preferences remained completely private and never shared with external AI services.

Our team worked closely with Interverse.ai's game designers and developers to understand their vision for adaptive gameplay. We discovered that their current system was generating massive amounts of player interaction data, but they lacked the intelligent layer that could process this data locally and create dynamic content in real-time. Our solution involved deploying Code Llama on their gaming infrastructure, creating a private AI system that could learn from player interactions locally and create adaptive game content without any external data sharing. The AI now creates dynamic NPCs, adapts environments based on player behavior, and learns from gameplay patterns, resulting in a 40% increase in player retention while keeping all player data completely private and secure.

Solution Approach

We deployed Code Llama on their gaming infrastructure, creating a private AI system that learns from player interactions locally and creates adaptive game content without any external data sharing.

Technical Implementation

Technologies & Tools

Code LlamaPythonUnityGame AnalyticsCustom ML

Results & Metrics

40% increase in player retention
Dynamic NPC behavior
2M+ daily active users
Complete player data privacy
Zhang Rui headshot

Case Study Author

Zhang Rui

Enterprise Delivery Director

Published

October 4, 2025