Arthur Engine
✨An open-source AI monitoring and governance engine providing LLM hallucination detection, PII identification, prompt injection defense, and traditional ML model evaluation, featuring real-time guardrails and OpenInference support.
An open-source AI monitoring and governance engine providing LLM hallucination detection, PII identification, prompt injection defense, and traditional ML model evaluation, featuring real-time guardrails and OpenInference support.
An interactive open-access textbook on Machine Learning Systems engineering from Harvard University, integrating the TinyTorch framework with hands-on edge deployment labs, covering the full spectrum from ML fundamentals to system optimization.
An AI-powered data science team of agents that automates data loading, cleaning, feature engineering, EDA, visualization, and machine learning modeling (H2O + MLflow) through specialized agent collaboration, featuring a Streamlit visual pipeline studio to perform common data science tasks 10X faster.
A modern AI gateway system that provides a unified OpenAI, Anthropic, Gemini and AI SDK compatible API, enabling seamless integration across multiple AI providers with automatic request translation and comprehensive tracing capabilities.
An AI agent framework built with Rust, powered by ICP blockchain and TEEs, designed to create a highly composable, autonomous, and perpetually memorizing network of AI agents.
An open-source AI agent platform offering no-code workflow building with dynamic graph-based solutions powered by the Actor Model, supporting multiple LLM integrations and real-time monitoring.
An LLM-powered retrieval engine designed to process extensive sources to collect comprehensive entity information, generating enriched tabular results rather than traditional research reports or answers.
A project focused on TTS generation models, providing an API server and Gradio-based WebUI with support for multiple voice synthesis, voice cloning, and audio enhancement capabilities.
A benchmark platform featuring 100 PhD-level research tasks across 22 distinct fields, systematically evaluating Deep Research Agents (DRAs) on report generation quality and information retrieval capabilities.
A knowledge base question-answering system built on large language models that supports document import and private model integration to quickly build knowledge base applications.
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