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.

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.