AI Answers & RAG Glossary: Essential Concepts for Developers and Teams

Clear definitions, practical examples and insights on Retrieval-Augmented Generation, AI workspaces, and large language models; built for developers, founders, and technical teams creating smarter AI systems.

Can geminı ai use google workspace

Yes, Gemini AI integrates with Google Workspace for enhanced productivity. Automatic reporting from Google Sheets & Analytics, email insights, and improved collaboration via Docs & Drive are possible.

What is rag in ai

RAG in AI (Retrieve, Aggregate, Generate) is a framework commonly used in advanced chatbots and question-answering systems. Retrieve fetches data, Aggregate organizes it, and Generate formulates human-like responses.

Unstructured Data vs. Structured Data

Structured data is organized and easily searchable, used in databases like SQL; it's ideal for structured queries and business intelligence. Unstructured data lacks a defined format, found in emails or multimedia.

What is hybrid search architecture in RAG: combining vector and metadata filtering?

Hybrid Search Architecture in Retrieval-Augmented Generation (RAG) models combine vector and metadata filtering. Initially, vector similarity search identifies relevant documents based on their vector representations. Subsequently, metadata filtering refi

Unify all your datasources and give your AI the context it needs.

Connect Google Drive, SharePoint, Notion, CRMs, wikis, and more—securely indexed and instantly usable in ChatGPT, Claude, Gemini, or any AI assistant.