AI Open-Source Project Directory

PT-Edge tracks 258,455 open-source AI projects across 30 domains, scored daily on maintenance, adoption, maturity, and community signals. Every project includes a practitioner-focused assessment — written for the person who has the problem, not the developer who built the tool.

Whether you're a scientist looking for a spectral analysis library, a trader evaluating backtesting engines, or an operations engineer hunting for anomaly detection — find the right tool, understand whether you can depend on it, and compare it against alternatives.

Browse by domain

ML Frameworks

55,638

Quality-scored directory of machine learning frameworks, training libraries, and ML infrastructure.

LLM Tools

30,160

Quality-scored directory of large language model tools, wrappers, and utilities.

AI Agents

27,421

Quality-scored directory of AI agent frameworks and tools, updated daily.

NLP Tools

19,556

Quality-scored directory of natural language processing tools and libraries.

Perception Tools

15,333

Quality-scored directory of web scraping, browser automation, and data extraction tools for AI agents.

MCP Servers

14,317

Quality-scored directory of MCP servers, updated daily.

RAG Tools

13,289

Quality-scored directory of retrieval-augmented generation tools, updated daily.

Voice AI Tools

10,624

Quality-scored directory of voice AI tools — TTS, STT, voice agents, and audio processing.

Generative AI Tools

10,188

Quality-scored directory of generative AI tools, chatbots, and content generation.

Transformer Models

9,484

Quality-scored directory of transformer models, fine-tuning tools, and inference engines.

AI Coding Tools

7,171

Quality-scored directory of AI-powered coding tools, updated daily.

Diffusion Models

5,599

Quality-scored directory of diffusion models and image generation tools.

Prompt Engineering Tools

5,239

Quality-scored directory of prompt engineering tools, frameworks, and libraries.

Embedding Tools

4,800

Quality-scored directory of embedding models, servers, and utilities.

Computer Vision Tools

4,158

Quality-scored directory of computer vision tools, models, and libraries.

Vector Databases

3,946

Quality-scored directory of vector databases and similarity search tools.

MLOps Tools

2,491

Quality-scored directory of MLOps tools for model deployment, monitoring, and lifecycle management.

Data Engineering Tools

1,482

Quality-scored directory of data engineering tools, pipelines, and ETL frameworks.

LLM Inference Engines

0

Quality-scored directory of LLM inference engines and local model runners, updated daily.

AI Evaluation Tools

0

Quality-scored directory of AI evaluation, benchmarking, and observability tools, updated daily.

Fine-Tuning Tools

0

Quality-scored directory of LLM and model fine-tuning tools, updated daily.

Document AI Tools

0

Quality-scored directory of document parsing, OCR, and data extraction tools, updated daily.

AI Safety Tools

0

Quality-scored directory of AI safety, guardrails, and security tools, updated daily.

Recommendation Systems

0

Quality-scored directory of recommendation system libraries, updated daily.

Audio AI Tools

0

Quality-scored directory of audio AI tools for music generation, source separation, and audio classification, updated daily.

Synthetic Data Tools

0

Quality-scored directory of synthetic data generation and augmentation tools, updated daily.

Time Series Tools

0

Quality-scored directory of time series forecasting and analysis tools, updated daily.

Multimodal AI Tools

0

Quality-scored directory of multimodal AI and vision-language tools, updated daily.

3D AI Tools

0

Quality-scored directory of 3D AI tools for NeRF, gaussian splatting, and 3D reconstruction, updated daily.

Scientific ML Tools

0

Quality-scored directory of scientific machine learning tools, updated daily.

How it works

Quality scores

Every project scored 0-100 on maintenance, adoption, maturity, and community. Updated daily from live GitHub, PyPI, and npm data.

Problem briefs

Each project assessed for what real-world problem it solves, who would use it, and when to choose it — written for practitioners, not developers.

Adoption assessments

Dependability ratings from Production-ready to Stalled. Know whether you can bet your project on a tool before you invest time learning it.