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genai-llm-ml-case-studies

A collection of 500+ real-world ML & LLM system design case studies from 100+ companies.

Introduction

Introduction

The GenAI & LLM System Design repository is a comprehensive collection of over 500 real-world case studies showcasing how more than 100 companies implement machine learning (ML) and large language models (LLMs) in production. This repository serves as a valuable resource for AI/ML engineers, leaders, and technical teams looking to understand the practical applications of generative AI and LLMs.

Key Features:
  • Diverse Case Studies: Explore a wide range of case studies across various industries, including tech, e-commerce, media, and finance.
  • System Design Patterns: Learn about different system design patterns such as Retrieval-Augmented Generation (RAG), multi-agent systems, and human-in-the-loop approaches.
  • Industry Insights: Gain insights into how leading companies like GitHub, Slack, and GoDaddy are leveraging LLMs and generative AI to enhance their products and services.
  • Contributing Guidelines: The repository encourages contributions from the community to keep the case studies up-to-date and relevant.
Benefits:
  • Knowledge Sharing: This repository promotes knowledge sharing among AI practitioners and organizations, helping them to learn from each other's experiences.
  • Practical Applications: It provides practical insights into the deployment and optimization of LLMs and generative AI systems, making it easier for teams to implement these technologies effectively.
  • Community Engagement: By allowing contributions, the repository fosters a collaborative environment for continuous learning and improvement in the field of AI.
Highlights:
  • Latest Trends: Stay updated with the latest trends in LLM and generative AI implementations.
  • Real-World Examples: Access real-world examples that illustrate the challenges and solutions encountered by companies in their AI journeys.

Information

  • Publisher
    AISecKit
  • Websitegithub.com
  • Published date2025/04/28

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