PixelVisionAI is an embodied AI system that learns to play games using screen pixels and OS-level input only. No game APIs, no memory access, no cheats — just vision, decision-making, and interaction, like a human player.

A high-performance AI assistant for real-time gameplay analysis. Features tactical strategy suggestions, skill-gap detection, and personalized training loops to level up your rank.

A reinforcement learning project featuring an intelligent agent trained to navigate and complete levels in Super Mario Bros. using deep Q-learning and computer vision techniques.

A python library that provides a simulation environment for the traditional Nepali board game "Baghchal" using Gymnasium

Reference architecture for multimodal gaming AI using NVIDIA Triton Inference Server and Kubernetes

Machine learning agent and coaching system for Super Auto Pets using reinforcement learning and computer vision

This repository provides an AI-powered player engagement system with personalized recommendations, in-game rewards, and generative content for gaming scenarios.

Gameplay-Review-AI — A high-performance analytical tool using AI to evaluate gaming sessions. Provides data-driven insights on mechanics, strategy, and performance to help players optimize skills.