Open Source JavaScript Artificial Intelligence Software

The OpenClaw Mobile Dashboard. Monitor agent's real-time thoughts, actions, track token costs, and manage tasks from anywhere using your pocket-sized Mission Control.

Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher accuracy and 83%+ success on complex workflows. Developers can integrate via Python/TypeScript SDKs or REST API, with support for OpenAI, Claude, Gemini, LangChain, LlamaIndex, and CrewAI. Features include built-in authentication, multi-tenancy, hosted servers, Docker support, and enterprise security guardrails. Licensed under Apache 2.0, Klavis simplifies AI development by eliminating complex authentication management and enabling seamless workflow automation across multiple applications.

Run ML models entirely in your browser. Embeddings, vector search, LLM chat, vision, audio, agents, and structured output - all offline, all private. No servers. No API keys. Your data never leaves your device.

LOSS is a high-speed, "split-stack" financial dashboard designed to strip away market noise. By combining mathematically rigorous technical indicators with VADER-powered AI sentiment analysis, LOSS delivers objective, real-time Buy, Sell, or Hold verdicts in under two seconds. Wrapped in a distraction-free, "Brutalist" user interface, this tool is built for traders who rely on data, not hype. Modern financial websites are bloated with ads, conflicting opinions, and unnecessary jargon. LOSS solves this by automating the math and reading the news for you. Instead of a monolithic architecture, LOSS uses a Split-Stack approach: A Vercel Relay handles raw data fetching, bypassing CORS and rate limits. A Render Python Backend acts as the "Brain," executing heavy machine learning and NLP tasks. Try the live application in action here: https://loss-by-vignesh.vercel.app before downloading the source code Visit For More Details : https://github.com/Vignesh-72/Loss

Just download the above zip file, extract it first and then open the index.html file on internet browsers like Firefox ( preferable ) or Google Chrome. Also, keep NumLock ON while using the Numeric Keypad of any Keyboard. Can also attach an external USB keyboard, with seperate Numeric Keypad, if required. I have added some general guidelines for students, using these softwares, on the Wiki Page of this website. Please refer them for more instructions.

Just download the above zip file, extract it and then open the index.html file on internet browsers like Firefox ( preferable ) or Google Chrome. Also, please view and download my full collection of softwares for people with disabilities, here : https://sourceforge.net/projects/softwares-for-disabled-people/ This full collection also includes the Voice Accounting Software as well.

Just download the above zip file, extract it and then open the index.html file on internet browsers like Firefox ( preferable ) or Google Chrome.

Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new video frames and Pipeless takes care of everything else. You can easily use industry-standard models, such as YOLO, or load your custom model in one of the supported inference runtimes. Pipeless ships some of the most popular inference runtimes, such as the ONNX Runtime, allowing you to run inference with high performance on CPU or GPU out-of-the-box. You can deploy your Pipeless application with a single command to edge and IoT devices or the cloud.