500-AI-Agents-Projects

Wed, 03 Sep 2025 15:26:44 +0800

ashishpatel26/500-AI-Agents-Projects

🌟 500+ AI Agent Projects / UseCases

A curated collection of AI agent use cases across industries, showcasing practical applications and linking to open-source projects for implementation. Explore how AI agents are transforming industries like healthcare, finance, education, and more! 🤖✨

📋 Table of Contents

🧠 Introduction

Artificial Intelligence (AI) agents are revolutionizing the way industries operate. From personalized learning to financial trading bots, AI agents bring efficiency, innovation, and scalability. This repository provides:

A categorized list of industries where AI agents are making an impact.
Detailed use cases with links to open-source projects for implementation.

Whether you’re a developer, researcher, or business enthusiast, this repository is your go-to resource for AI agent inspiration and learning.

🏭 Industry UseCase MindMap

🧩 Use Case Table

Use Case	Industry	Description
HIA (Health Insights Agent)	Healthcare	analyses medical reports and provide health insights.
AI Health Assistant	Healthcare	Diagnoses and monitors diseases using patient data.
Automated Trading Bot	Finance	Automates stock trading with real-time market analysis.
Virtual AI Tutor	Education	Provides personalized education tailored to users.
24/7 AI Chatbot	Customer Service	Handles customer queries around the clock.
Product Recommendation Agent	Retail	Suggests products based on user preferences and history.
Self-Driving Delivery Agent	Transportation	Optimizes routes and autonomously delivers packages.
Factory Process Monitoring Agent	Manufacturing	Monitors production lines and ensures quality control.
Property Pricing Agent	Real Estate	Analyzes market trends to determine property prices.
Smart Farming Assistant	Agriculture	Provides insights on crop health and yield predictions.
Energy Demand Forecasting Agent	Energy	Predicts energy usage to optimize grid management.
Content Personalization Agent	Entertainment	Recommends personalized media based on preferences.
Legal Document Review Assistant	Legal	Automates document review and highlights key clauses.
Recruitment Recommendation Agent	Human Resources	Suggests best-fit candidates for job openings.
Virtual Travel Assistant	Hospitality	Plans travel itineraries based on preferences.
AI Game Companion Agent	Gaming	Enhances player experience with real-time assistance.
Real-Time Threat Detection Agent	Cybersecurity	Identifies potential threats and mitigates attacks.
E-commerce Personal Shopper Agent	E-commerce	Helps customers find products they’ll love.
Logistics Optimization Agent	Supply Chain	Plans efficient delivery routes and manages inventory.
Vibe Hacking Agent	Cybersecurity	Autonomous Multi-Agent Based Red Team Testing Service.
MediSuite-Ai-Agent	Health insurance	A medical ai agent that helps automating the process of hospitals / insurance claiming workflow.
Lina-Egyptian-Medical-Chatbot	Health insurance	A medical ai agent that helps automating the process of hospitals / insurance claiming workflow.

Framework wise Usecases

Framework Name: CrewAI

Use Case	Industry	Description
📧 Email Auto Responder Flow	🗣️ Communication	Automates email responses based on predefined criteria to enhance communication efficiency.
📝 Meeting Assistant Flow	🛠️ Productivity	Assists in organizing and managing meetings, including scheduling and agenda preparation.
🔄 Self Evaluation Loop Flow	👥 Human Resources	Facilitates self-assessment processes within an organization, aiding in performance reviews.
📈 Lead Score Flow	💼 Sales	Evaluates and scores potential leads to prioritize outreach in sales strategies.
📊 Marketing Strategy Generator	📢 Marketing	Develops marketing strategies by analyzing market trends and audience data.
📝 Job Posting Generator	🧑‍💼 Recruitment	Creates job postings by analyzing job requirements, aiding in recruitment processes.
🔄 Recruitment Workflow	🧑‍💼 Recruitment	Streamlines the recruitment process by automating various tasks involved in hiring.
🔍 Match Profile to Positions	🧑‍💼 Recruitment	Matches candidate profiles to suitable job positions to enhance recruitment efficiency.
📸 Instagram Post Generator	📱 Social Media	Generates and schedules Instagram posts automatically, streamlining social media management.
🌐 Landing Page Generator	💻 Web Development	Automates the creation of landing pages for websites, facilitating web development tasks.
🎮 Game Builder Crew	🎮 Game Development	Assists in the development of games by automating certain aspects of game creation.
💹 Stock Analysis Tool	💰 Finance	Provides tools for analyzing stock market data to assist in financial decision-making.
🗺️ Trip Planner	✈️ Travel	Assists in planning trips by organizing itineraries and managing travel details.
🎁 Surprise Trip Planner	✈️ Travel	Plans surprise trips by selecting destinations and activities based on user preferences.
📚 Write a Book with Flows	✍️ Creative Writing	Assists authors in writing books by providing structured workflows and writing assistance.
🎬 Screenplay Writer	✍️ Creative Writing	Aids in writing screenplays by offering templates and guidance for script development.
✅ Markdown Validator	📄 Documentation	Validates Markdown files to ensure proper formatting and adherence to standards.
🧠 Meta Quest Knowledge	📚 Knowledge Management	Manages and organizes knowledge related to Meta Quest, facilitating information retrieval.
🤖 NVIDIA Models Integration	🤖 AI Integration	Integrates NVIDIA AI models into workflows to enhance computational capabilities.
🗂️ Prep for a Meeting	🛠️ Productivity	Assists in preparing for meetings by organizing materials and setting agendas.
🛠️Starter Template	🛠️ Development	Provides a starter template for new projects to streamline the setup process.
🔗CrewAI + LangGraph Integration	🤖 AI Integration	Demonstrates integration between CrewAI and LangGraph for enhanced workflow automation.

Framework Name: Autogen

Code Generation, Execution, and Debugging

Use Case	Industry	Description
🤖 Automated Task Solving with Code Generation, Execution & Debugging	💻 Software Development	Demonstrates automated task-solving by generating, executing, and debugging code.
🧑‍💻 Automated Code Generation and Question Answering with Retrieval Augmented Agents	💻 Software Development	Generates code and answers questions using retrieval-augmented methods.
🧠 Automated Code Generation and Question Answering with Qdrant-based Retrieval	💻 Software Development	Utilizes Qdrant for enhanced retrieval-augmented agent performance.

Multi-Agent Collaboration (>3 Agents)

Use Case	Industry	Description
🤝 Automated Task Solving by Group Chat (3 members, 1 manager)	🤝 Collaboration	Demonstrates group task-solving via multi-agent collaboration.
📊 Automated Data Visualization by Group Chat (3 members, 1 manager)	📊 Data Analysis	Uses multi-agent collaboration to create data visualizations.
🧩 Automated Complex Task Solving by Group Chat (6 members, 1 manager)	🤝 Collaboration	Solves complex tasks collaboratively with a larger group of agents.
🧑‍💻 Automated Task Solving with Coding & Planning Agents	🛠️ Planning & Development	Combines coding and planning agents for solving tasks effectively.
📐 Automated Task Solving with Transition Paths Specified in a Graph	🤝 Collaboration	Uses predefined transition paths in a graph for solving tasks.
🧠 Running a Group Chat as an Inner-Monologue via the SocietyOfMindAgent	🧠 Cognitive Sciences	Simulates inner-monologue for problem-solving using group chats.
🔧 Running a Group Chat with Custom Speaker Selection Function	🤝 Collaboration	Implements a custom function for speaker selection in group chats.

Sequential Multi-Agent Chats

Use Case	Industry	Description
🔄 Solving Multiple Tasks in a Sequence of Chats Initiated by a Single Agent	🔄 Workflow Automation	Automates sequential task-solving with a single initiating agent.
⏳ Async-solving Multiple Tasks in a Sequence of Chats Initiated by a Single Agent	🔄 Workflow Automation	Handles asynchronous task-solving in a sequence of chats initiated by one agent.
🤝 Solving Multiple Tasks in a Sequence of Chats Initiated by Different Agents	🔄 Workflow Automation	Facilitates sequential task-solving with different agents initiating each chat.

Nested Chats

Use Case	Industry	Description
🧠 Solving Complex Tasks with Nested Chats	🧠 Problem Solving	Uses nested chats to solve hierarchical and complex problems.
🔄 Solving Complex Tasks with A Sequence of Nested Chats	🧠 Problem Solving	Demonstrates sequential task-solving using nested chats.
🏭 OptiGuide for Solving a Supply Chain Optimization Problem with Nested Chats	🏭 Supply Chain Optimization	Showcases how to solve supply chain optimization problems using nested chats, a coding agent, and a safeguard agent.
♟️ Conversational Chess with Nested Chats and Tool Use	🎮 Gaming	Explores the use of nested chats for playing conversational chess with integrated tools.

Application

Use Case	Industry	Description
🔄 Automated Continual Learning from New Data	📊 Machine Learning	Continuously learns from new data inputs for adaptive AI.
🏭 OptiGuide - Coding, Tool Using, Safeguarding & Question Answering for Supply Chain Optimization	🏭 Supply Chain Optimization	Highlights a solution combining coding, tool use, and safeguarding for supply chain optimization.
🤖 AutoAnny - A Discord bot built using AutoGen	💬 Communication Tools	Showcases the development of a Discord bot using AutoGen for enhanced interaction.

Tools

Use Case	Industry	Description
🌐 Web Search: Solve Tasks Requiring Web Info	🔍 Information Retrieval	Searches the web to gather information required for completing tasks.
🔧 Use Provided Tools as Functions	🛠️ Tool Integration	Demonstrates how to use pre-provided tools as callable functions in AutoGen.
🔗 Use Tools via Sync and Async Function Calling	🛠️ Tool Integration	Illustrates synchronous and asynchronous tool usage within AutoGen workflows.
🧩 Task Solving with Langchain Provided Tools as Functions	🔍 Language Processing	Leverages Langchain tools for task-solving within AutoGen.
📚 RAG: Group Chat with Retrieval Augmented Generation	🤝 Collaboration	Enables group chat with Retrieval Augmented Generation (RAG) to support information sharing.
⚙️ Function Inception: Update/Remove Functions During Conversations	🔧 Development Tools	Allows AutoGen agents to modify their functions dynamically during conversations.
🔊 Agent Chat with Whisper	🎙️ Audio Processing	Demonstrates AI agent capabilities for transcription and translation using Whisper.
📏 Constrained Responses via Guidance	💡 Natural Language Processing	Shows how to use guidance to constrain responses generated by agents.
🌍 Browse the Web with Agents	🌐 Information Retrieval	Explains how to configure agents to browse and retrieve information from the web.
📊 SQL: Natural Language Text to SQL Query Using Spider Benchmark	💾 Database Management	Converts natural language inputs into SQL queries using the Spider benchmark.
🕸️ Web Scraping with Apify	🌐 Data Gathering	Illustrates web scraping techniques with Apify using AutoGen.
🕷️ Web Crawling: Crawl Entire Domain with Spider API	🌐 Data Gathering	Explains how to crawl entire domains using the Spider API.
💻 Write a Software App Task by Task with Specially Designed Functions	💻 Software Development	Builds a software application step-by-step using designed functions.

Human Development

Use Case	Industry	Description
💬 Simple Example in ChatGPT Style	🧠 Conversational AI	Demonstrates a simple conversational example in the style of ChatGPT.
🤖 Auto Code Generation, Execution, Debugging and Human Feedback	💻 Software Development	Showcases code generation, execution, debugging with human feedback integrated into the workflow.
👥 Automated Task Solving with GPT-4 + Multiple Human Users	🤝 Collaboration	Enables task solving with multiple human users collaborating with GPT-4.
🔄 Agent Chat with Async Human Inputs	🧠 Conversational AI	Supports asynchronous human input during agent conversations.

Agent Teaching and Learning

Use Case	Industry	Description
📘 Teach Agents New Skills & Reuse via Automated Chat	🎓 Education & Training	Demonstrates teaching new skills to agents and enabling their reuse in automated chats.
🧠 Teach Agents New Facts, User Preferences and Skills Beyond Coding	🎓 Education & Training	Shows how to teach agents new facts, user preferences, and non-coding skills.
🤖 Teach OpenAI Assistants Through GPTAssistantAgent	💻 AI Assistant Development	Illustrates how to enhance OpenAI assistants’ capabilities using GPTAssistantAgent.
🔄 Agent Optimizer: Train Agents in an Agentic Way	🛠️ Optimization	Explains how to train agents effectively in an agentic manner using the Agent Optimizer.

Multi-Agent Chat with OpenAI Assistants in the loop

Use Case	Industry	Description
🌟 Hello-World Chat with OpenAI Assistant in AutoGen	🤖 Conversational AI	A basic example of chatting with OpenAI Assistant using AutoGen.
🔧 Chat with OpenAI Assistant using Function Call	🔧 Development Tools	Illustrates how to use function calls with OpenAI Assistant in chats.
🧠 Chat with OpenAI Assistant with Code Interpreter	💻 Software Development	Demonstrates the use of OpenAI Assistant as a code interpreter in chats.
🔍 Chat with OpenAI Assistant with Retrieval Augmentation	📚 Information Retrieval	Enables retrieval-augmented conversations with OpenAI Assistant.
🤝 OpenAI Assistant in a Group Chat	🤝 Collaboration	Shows how OpenAI Assistant can collaborate with other agents in a group chat.
🛠️ GPTAssistantAgent based Multi-Agent Tool Use	🔧 Development Tools	Explains how to use GPTAssistantAgent for multi-agent tool usage.

Non-OpenAI Models

Use Case	Industry	Description	Notebook
♟️ Conversational Chess using Non-OpenAI Models	🎮 Gaming	Explores conversational chess implemented with non-OpenAI models.

Multimodal Agent

Use Case	Industry	Description
🎨 Multimodal Agent Chat with DALLE and GPT-4V	🖼️ Multimedia AI	Combines DALLE and GPT-4V for multimodal agent communication.
🖌️ Multimodal Agent Chat with Llava	📷 Image Processing	Uses Llava for enabling multimodal agent conversations with image processing.
🖼️ Multimodal Agent Chat with GPT-4V	🖼️ Multimedia AI	Leverages GPT-4V for visual and conversational interactions in multimodal agents.

Long Context Handling

Use Case	Industry	Description	Notebook
📜 Long Context Handling as A Capability	🧠 AI Capability	Demonstrates techniques for handling long context effectively within AI workflows.

Evaluation and Assessment

Use Case	Industry	Description	Notebook
📊 AgentEval: A Multi-Agent System for Assessing Utility of LLM-Powered Applications	📈 Performance Evaluation	Introduces AgentEval for evaluating and assessing the performance of LLM-based applications.

Automatic Agent Building

Use Case	Industry	Description	Notebook
🏗️ Automatically Build Multi-agent System with AgentBuilder	🤖 AI Development	Explains how to automatically build multi-agent systems using the AgentBuilder tool.
📚 Automatically Build Multi-agent System from Agent Library	🤖 AI Development	Shows how to construct multi-agent systems by leveraging a pre-defined agent library.

Observability

Use Case	Industry	Description	Notebook
📊 Track LLM Calls, Tool Usage, Actions and Errors using AgentOps	📈 Monitoring & Analytics	Demonstrates how to monitor LLM interactions, tool usage, and errors using AgentOps.

Enhanced Inferences

Use Case	Industry	Description
🔗 API Unification	🔧 API Management	Explains how to unify API usage with documentation and code examples.
⚙️ Utility Functions to Help Managing API Configurations Effectively	🔧 API Management	Demonstrates utility functions to manage API configurations more effectively.
💰 Cost Calculation	📈 Cost Management	Introduces methods for tracking token usage and estimating costs for LLM interactions.
⚡ Optimize for Code Generation	📊 Optimization	Highlights cost-effective optimization techniques for improving code generation with LLMs.
📐 Optimize for Math	📊 Optimization	Explains techniques to optimize LLM performance for solving mathematical problems.

Framework Name: Agno

UseCase

Use Case	Industry	Description
🤖 Support Agent	💻 Software Development / AI / Framework Support	The Agno Support Agent helps developers with the Agno framework by providing real-time answers, explanations, and code examples.
🎥 YouTube Agent	📺 Media & Content	An intelligent agent that analyzes YouTube videos by generating detailed summaries, timestamps, themes, and content breakdowns using AI tools.
📊 Finance Agent	💼 Finance	An advanced AI-powered market analyst that delivers real-time stock market insights, analyst recommendations, financial deep-dives, and sector-specific trends. Supports prompts for detailed analysis of companies like AAPL, TSLA, NVDA, etc.
📚 Study Partner	🎓 Education	Assists users in learning by finding resources, answering questions, and creating study plans.
🛍️ Shopping Partner Agent	🏬 E-commerce	A product recommender agent that helps users find matching products based on preferences from trusted platforms like Amazon, Flipkart, etc.
🎓 Research Scholar Agent	🧠 Education / Research	An AI-powered academic assistant that performs advanced academic searches, analyzes recent publications, synthesizes findings across disciplines, and writes well-structured academic reports with proper citations.
🧠 Research Agent	🗞️ Media & Journalism	A research agent that combines web search and professional journalistic writing. It performs deep investigations and produces NYT-style reports.
🍳 Recipe Creator	🍽️ Food & Culinary	An AI-powered recipe recommendation agent that provides personalized recipes based on ingredients, preferences, and time constraints.
🗞️ Finance Agent	💼 Finance	A powerful financial analyst agent combining real-time stock data, analyst insights, company fundamentals, and market news. Ideal for analyzing companies like Apple, Tesla, NVIDIA, and sectors like semiconductors or automotive.
🧠 Financial Reasoning Agent	📈 Finance	Uses a Claude-3.5 Sonnet-based agent to analyze stocks like NVDA using tools for reasoning and Yahoo Finance data.
🤖 Readme Generator Agent	💻 Software Dev	Agent generates high-quality READMEs for GitHub repositories using repo metadata.
🎬 Movie Recommendation Agent	🎥 Entertainment	An intelligent agent that gives personalized movie recommendations using Exa and GPT-4o, analyzing genres, themes, and latest ratings.
🔍 Media Trend Analysis Agent	📰 Media & News	Analyzes emerging trends, patterns, and influencers from digital platforms using AI-powered agents and scraping.
⚖️ Legal Document Analysis Agent	🏛️ Legal Tech	An AI agent that analyzes legal documents from PDF URLs and provides legal insights based on a knowledge base using vector embeddings and GPT-4o.
🤔 DeepKnowledge	🧠 Research	This agent performs iterative searches through its knowledge base, breaking down complex queries into sub-questions and synthesizing comprehensive answers. It uses Agno docs for demonstration and is designed for deep reasoning and exploration.
📚 Book Recommendation Agent	🧠 Publishing & Media	An intelligent agent that provides personalized book suggestions using literary data, reader preferences, reviews, and release info.
🏠 MCP Airbnb Agent	🛎️ Hospitality	Create an AI Agent using MCP and Llama 4 to search Airbnb listings with filters like workspace & transport proximity.
🤖 Assist Agent	🧠 AI Framework	An AI agent using GPT-4o to answer questions about the Agno framework with hybrid search and embedded knowledge.

Framework Name: Langgraph

UseCase

Use Case	Industry	Description
🤖 Chatbot Simulation Evaluation	💻 💬 AI / Quality Assurance	Simulate user interactions to evaluate chatbot performance, ensuring robustness and reliability in real-world scenarios.
🧠 Information Gathering via Prompting	🧠 AI / Research & Development	This tutorial demonstrates how to design a LangGraph workflow that utilizes prompting techniques to gather information effectively. It showcases how to structure prompts and manage the flow of information to build intelligent agents.
🧠 Code Assistant with LangGraph	💻 Software Development	This tutorial demonstrates how to build a resilient code assistant using LangGraph. It guides you through creating a graph-based agent that can handle code generation, error checking, and iterative refinement, ensuring robust and accurate coding assistance.
🧑‍💼 Customer Support Agent	🧑‍💼 Customer Support Agent	This tutorial demonstrates how to build a customer support agent using LangGraph. It guides you through creating a graph-based agent that can handle customer inquiries, providing automated support and enhancing user experience.
🔁 Extraction with Retries	🧠 AI / Data Extraction	This tutorial demonstrates how to implement retry mechanisms in LangGraph workflows, ensuring robust data extraction processes that can handle transient errors and improve reliability.
🧠 Multi-Agent Workflow	🧠 AI / Workflow Orchestration	This tutorial demonstrates how to build a multi-agent system using LangGraph’s agent supervisor. It guides you through creating a supervisor agent that orchestrates multiple specialized agents, managing task delegation and communication flow.
🧠 Hierarchical Agent Teams	🧠 AI / Workflow Orchestration	This tutorial demonstrates how to build a hierarchical agent system using LangGraph. It guides you through creating a top-level supervisor agent that delegates tasks to specialized sub-agents, enabling complex workflows with clear task delegation and communication.
🤝 Multi-Agent Collaboration	🧠 AI / Workflow Orchestration	This tutorial demonstrates how to implement multi-agent collaboration using LangGraph. It guides you through creating multiple specialized agents that work together to accomplish a complex task, showcasing the power of agent collaboration in AI workflows.
🧠 Plan-and-Execute Agent	🧠 AI / Workflow Orchestration	This tutorial demonstrates how to build a “Plan-and-Execute” style agent using LangGraph. It guides you through creating an agent that first generates a multi-step plan and then executes each step sequentially, revisiting and modifying the plan as necessary. This approach is inspired by the Plan-and-Solve paper and the Baby-AGI project, aiming to enhance long-term planning and task execution in AI workflows.
🧠 SQL Agent	🧠 AI / Database Interaction	This tutorial demonstrates how to build an agent that can answer questions about a SQL database. The agent fetches available tables, determines relevance to the question, retrieves schemas, generates a query, checks for errors, executes it, and formulates a response.
🧠 Reflection Agent	🧠 AI / Workflow Orchestration	This tutorial demonstrates how to build a reflection agent using LangGraph. It guides you through creating an agent that can critique and revise its own outputs, enhancing the quality and reliability of generated content.
🧠 Reflexion Agent	🧠 AI / Workflow Orchestration	This tutorial demonstrates how to build a reflexion agent using LangGraph. It guides you through creating an agent that can reflect on its actions and outcomes, enabling iterative improvement and more accurate decision-making in complex workflows.
LangGraph Agentic RAG
🧠 Adaptive RAG	🧠 AI / Information Retrieval	This tutorial demonstrates how to build an Adaptive RAG system using LangGraph. It guides you through creating a dynamic retrieval process that adjusts based on query complexity, enhancing the efficiency and accuracy of information retrieval.
🧠 Adaptive RAG (Local)	🧠 AI / Information Retrieval	This tutorial focuses on implementing Adaptive RAG with local models, allowing for offline retrieval and generation, which is crucial for environments with limited internet access or privacy concerns.
🤖 Agentic RAG	🤖 AI / Intelligent Agents	Learn to build an Agentic RAG system where an agent determines the best retrieval strategy before generating a response, improving the relevance and accuracy of answers.
🤖 Agentic RAG (Local)	🤖 AI / Intelligent Agents	This tutorial extends Agentic RAG to local environments, enabling the use of local models and data sources for retrieval and generation tasks.
🧠 Corrective RAG (CRAG)	🧠 AI / Information Retrieval	Implement a Corrective RAG system that evaluates and refines retrieved documents before passing them to the generator, ensuring higher-quality outputs.
🧠 Corrective RAG (Local)	🧠 AI / Information Retrieval	This tutorial focuses on building a Corrective RAG system using local resources, allowing for offline document evaluation and refinement processes.
🧠 Self-RAG	🧠 AI / Information Retrieval	Learn to implement Self-RAG, where the system reflects on its responses and retrieves additional information if necessary, enhancing the accuracy and relevance of generated content.
🧠 Self-RAG (Local)	🧠 AI / Information Retrieval	This tutorial demonstrates how to implement Self-RAG using local models and data sources, enabling offline reflection and retrieval processes.

🤝 Contributing

Contributions are welcome! 🎉 Here’s how you can help:

Fork the repository.
Add a new use case or improve an existing one.
Submit a pull request with your changes.

Please follow our Contributing Guidelines for more details.

📜 License

This repository is licensed under the MIT License. See the LICENSE file for more information.

🚀 Let’s Build Together!

Feel free to share this repository with your network and star ⭐ it if you find it useful. Let’s collaborate to create the ultimate resource for AI agent use cases!

deep-prove

Thu, 29 May 2025 15:30:17 +0800

Lagrange-Labs/deep-prove

🚀 DeepProve: Zero-Knowledge Machine Learning (zkml) Inference

Welcome to DeepProve, a cutting-edge framework designed to prove neural network inference using zero-knowledge cryptographic techniques. Whether you’re working with Multi-Layer Perceptrons (MLPs) or Convolutional Neural Networks (CNNs), DeepProve offers a fast and efficient way to verify computations without revealing the underlying data. zkml is the name of the subcrate implementing the proving logic.

🤔 What Does DeepProve Do?

DeepProve leverages advanced cryptographic methods like sumchecks and logup GKR to achieve sublinear proving times. This means you can prove the correctness of your model’s inference faster than ever before!

📊 Benchmark Highlights

CNN 264k: This runs a CNN on the cifar 10 dataset for a total of 264k parameters. DeepProve is proving 158x faster at this size! Dense 4M: This runs a multiple dense layers for a total of 4 million parameters. DeepProve is proving 54x faster at this size!

Model Type	ZKML Proving Time (ms)	ZKML Verification Time (ms)	EZKL Proving Time (ms)	EZKL Verification Time (ms)
CNN 264k	1242	599	196567.01	312505
Dense 4M	2335	520	126831.3	1112

📜 Licensing

zkml folder: Licensed under the Lagrange License, unless otherwise specified.
Rest of the Code: Licensed under Apache 2.0 + MIT, as per the original repository.

🌟 Use Cases

Proving inference of AI models has a wide range of applications, especially in scenarios where privacy and trust are paramount. For instance, in healthcare, sensitive patient data can be used to make predictions without exposing the data itself. In finance, models can be verified for compliance without revealing proprietary algorithms. Additionally, in decentralized applications, zero-knowledge proofs can ensure the integrity of AI computations on the blockchain, fostering trust and transparency. These use cases highlight the transformative potential of ZKML in various industries.

🙏 Acknowledgements

This project builds upon the work from scroll-tech/ceno, reusing the sumcheck and GKR implementation from their codebase. Check out their work at scroll-tech/ceno.

For more technical details and usage instructions, dive into the ZKML README.

Happy proving! 🎉

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