AgenticRAG provides a modular architecture for creating autonomous agents that leverage retrieval-augmented generation (RAG). It offers components to index documents in vector stores, retrieve relevant context, and feed it into LLMs to generate context-aware responses. Users can integrate external APIs and tools, configure memory stores to track conversation history, and define custom workflows to orchestrate multi-step decision-making processes. The framework supports popular vector databases like Pinecone and FAISS, and LLM providers such as OpenAI, allowing seamless switching or multi-model setups. With built-in abstractions for agent loops and tool management, AgenticRAG simplifies development of agents capable of tasks like document QA, automated research, and knowledge-driven automation, reducing boilerplate code and accelerating time to deployment.

GPTURER is an AI tool designed to streamline the creation of knowledge datasets by extracting text, images, and URLs from websites. These datasets can then be integrated into ChatGPT, enhancing its performance and capabilities. In just a few steps, users can scan websites and convert the content into structured output files, making it an efficient solution for crafting personalized ChatGPT assistants.

Kaila.ai is an innovative AI platform that quickly absorbs and organizes company-specific knowledge. By leveraging advanced algorithms, it delivers precise and instant answers to queries. Ideal for organizations aiming to improve efficiency by integrating this conversational AI assistant, Kaila.ai supports the creation of custom datasets and the training of AI models tailored to company-specific topics.

SciPhi is an open-source platform designed to simplify the building, deploying, and scaling of Retrieval-Augmented Generation (RAG) systems. It provides an end-to-end solution for developers, enabling them to focus on AI innovation without worrying about the underlying infrastructure. With tools for automated knowledge graph extraction, document and user management, and robust observability, SciPhi ensures efficient and optimized RAG system deployment.