A comprehensive machine learning and math framework for Go, providing a PyTorch-like experience with support for XLA, ONNX, and pure Go backends.

A collective communications library that provides primitives like allreduce and broadcast for efficient multi-machine machine learning training.

A JavaScript SDK that enables running production-ready LLMs and multimodal AI models directly in the browser using WebGPU acceleration for privacy and zero server costs.

An autoresearch orchestrator that automates code optimization by running parallel AI-driven experiments in a loop to iteratively improve codebase metrics.

A high-performance library for approximate nearest neighbor searches in high-dimensional vector spaces, supporting graph and tree-based indexing for datasets up to billions of objects.

A universal workflow plugin for Claude Code and other AI agents that provides specialized agents, slash commands, and automation hooks to streamline software development.

A collection of custom scikit-learn compatible transformers, metrics, and models to extend the functionality of machine learning pipelines.

An ML-based tool for master data management and entity resolution that deduplicates and links records across disparate data sources at scale.

A Python library that turns an Android device into a Reinforcement Learning environment, allowing agents to learn to navigate the OS and apps via touchscreen interactions.

A comprehensive Python library of 233+ meta-heuristic algorithms for solving complex global optimization problems and tuning AI/ML parameters.

A Python library for offline reinforcement learning that provides a standardized way to load, create, and manage experience datasets.

A toolkit for converting dataset annotations from JSON formats like COCO and LabelMe into the YOLO format for object detection training.

A comprehensive benchmarking framework for Brain-Computer Interface (BCI) algorithms applied to freely available EEG datasets to ensure research reproducibility.

A web-based visual interface and logger for Claude Code that adds a GUI, code diffing, and mobile access to the terminal-based AI coding tool.

A library for evaluating AI model outputs using LLM-as-a-judge, RAG-specific metrics, and heuristic methods through a unified interface.

TenSEAL is a Python library for homomorphic encryption on tensors, built on Microsoft SEAL. It lets you run arithmetic operations on encrypted data, enabling privacy-preserving machine learning without exposing raw information.

A serverless Python runtime and client library for deploying and scaling ML models and pipelines in the cloud without managing infrastructure.

Cellm is an Excel add‑in that adds a `=PROMPT()` formula, letting users call LLMs (hosted or local) on cell ranges to automate data‑cleaning, extraction, translation, summarisation, and other repetitive tasks directly inside spreadsheets.

An enterprise AI resource management platform that helps organizations control AI costs, manage model access, and quantify AI productivity through centralized identity and budget tracking.

A deep learning toolbox for predicting quantum-chemical properties of molecules and materials using atomistic neural networks.

Nengo is a Python library for building and simulating large-scale neural models, supporting both spiking and non-spiking simulations.

A PyTorch-based deep learning library for Graph and Hypergraph Neural Networks that supports high-order message passing and Auto-ML tuning.

A library for simplifying the fine-tuning, inference, and retrieval of ColBERT late interaction models, providing high-speed indexing and flexible training options.

An open-source inference server that provides a standardized REST and gRPC interface for serving machine learning models across various frameworks.

A diverse suite of scalable, hardware-accelerated reinforcement learning environments written in JAX for high-speed RL research and experimentation.

An open-source engine for fine-tuning and serving large language models, providing tools to deploy models on hosted or self-managed Kubernetes infrastructure.

An MCP server that gives AI coding agents runtime access to Phoenix applications, allowing them to execute code, query databases, and read live logs during development.

A code intelligence CLI tool that combines AST-based call graph analysis and hybrid semantic search to help developers and AI agents navigate large codebases.

A framework for integrating machine learning into LLVM to replace human-crafted compiler optimization heuristics with trained models.

A modular deep learning extension for PyTorch designed to build neural network models on heterogeneous tabular data containing mixed column types like text, images, and numerical values.

An open source agent engineering platform for collaboratively tracing, evaluating, monitoring, and debugging AI agents.

An MCP server that enables LLMs to manage Docker containers, images, and volumes using natural language commands.

A Swift package for effortless interaction with OpenAI's API and other OpenAI-compatible providers, supporting text, image, audio, and real-time voice conversations.

A neural texture compression SDK that compresses multiple PBR texture channels into a single neural set to reduce VRAM and bandwidth usage in 3D rendering.

An MCP server that gives AI agents unfiltered access to a local shell and file system for autonomous coding, building, and running of software.

An OpenRouter provider for the Vercel AI SDK that enables access to 300+ LLMs and embedding models through a unified interface.

A library that converts scikit-learn models to the ONNX format, enabling high-performance inference using ONNX Runtime.

A private, browser-native AI studio and agent workspace that runs LLMs locally on your device using WebGPU, requiring no API keys or backend servers.

A proxy that sits between AI agents and LLM APIs to compress conversation history in the background, preventing delays when context limits are are reached.

An MCP server that connects AI assistants to Google Docs, Sheets, Drive, Gmail, and Calendar, enabling LLMs to read and manage Workspace data.

A lightweight, OpenAI-compatible AI SDK designed for minimal bundle size and high portability across browser, edge, and agent tooling.

An AI-powered plugin for the Fish shell that converts natural language comments to shell commands, provides autocompletions, and suggests fixes for broken commands.

A Python library for securely persisting and sharing scikit-learn models without using pickle, including tools for creating model cards.

A foundation model for multivariate time series forecasting optimized for observability metrics, providing zero-shot and probabilistic predictions.

A local orchestration tool that uses multiple AI subscriptions to provide parallel, multi-vendor code reviews to catch bugs and biases that a single AI model would miss.

A PyTorch library that implements per-step fault tolerance for large-scale training, allowing jobs to continue running even when individual workers or nodes fail.

A tool for simplifying and slimming ONNX models to reduce operator count and improve inference speed while maintaining accuracy.

A memory manager for LLM KV-caches that uses CUDA virtual memory APIs to enable dynamic allocation while maintaining virtual contiguity for unmodified attention kernels.