Explore 2764+ AI Developers (page 183)
Boost.space
Boost.space is a cloud database and integration platform that synchronizes data across over 2,500 tools to create a Single Source of Truth for AI and automation.
Top Online
To provide transparent, automated yet human-centric SEO services that deliver measurable results for e-commerce through white-hat methods and AI-driven monitoring.
HostedClaws
HostedClaws makes running AI agents simple by providing a managed, private cloud environment for AI assistants without the need for servers, Docker, or API keys.
Figrfast Systems Private Limi…
To transform the product design process by leveraging product-aware AI that understands context, UX reasoning, and existing design systems.
Subterranean
To democratize the creation of AI-native businesses by providing a platform where AI agents collaborate as technical co-founders to build and manage applications.
Synra
Provide a simple, secure, and managed way to connect AI agents like Claude to SQL databases in under 60 seconds.
woocassh
woocassh builds open-source tools for AI agent management. The developer created VidClaw as a self-hosted dashboard to manage OpenClaw agents after finding chat-based management too chaotic. The project focuses on visual task queuing, usage tracking, and agent personality customization.
matt1398
matt1398 develops claude-devtools, an open-source desktop application for inspecting Claude Code sessions. The project provides developers with complete visibility into AI coding assistant activity through session log analysis.
ggml-org
ggml-org develops high-performance machine learning inference libraries in C/C++. The organization maintains llama.cpp, one of the most popular open-source projects for running large language models locally. The team focuses on creating efficient, portable implementations that enable AI inference across diverse hardware platforms without heavy dependencies.
Apple ML Explore
Apple ML Explore develops open-source machine learning tools and frameworks optimized for Apple Silicon. The team builds MLX, a NumPy-like array framework designed for efficient machine learning on Apple devices, along with companion libraries like MLX LM for language models. Their work focuses on enabling developers to run and train ML models locally on Mac hardware with high performance.