What is AI Knowledge Base (RAG)?
🚀 We’re excited to launch AI Knowledge Base — a drag-and-drop RAG tool that turns your files into a smart knowledge repository. Together with prompt engineering, model switching, logging & more, building AI is now effortless.
Problem
Users manually set up RAG systems, requiring technical expertise and time-consuming integration of components. Key drawbacks: manual setup of RAG systems, complex integration of components, and lack of intuitive interfaces.
Solution
A drag-and-drop RAG tool enabling users to build AI knowledge bases by uploading files, connecting data sources, and customizing prompts. Core: visual workflow builder, model switching, and automated prompt engineering.
Customers
AI developers, data scientists, and product managers in startups or SMEs needing no-code RAG solutions. Demographics: tech-savvy professionals aged 25-45 prioritizing rapid AI prototyping.
Unique Features
No-code visual RAG pipeline builder, real-time collaboration, and seamless integration with LLMs (e.g., GPT-4, Claude) and file formats (PDFs, spreadsheets).
User Comments
Saves weeks of development time
Intuitive for non-coders
Flexible model options
Prompt templates accelerate deployment
Debugging logs need improvement
Traction
Launched 3 months ago; 1,200+ active users, 450+ teams. Features: version control (added 2 weeks ago), Slack integration (launched last month). Founder has 2.3K followers on LinkedIn.
Market Size
The global AI knowledge management market is projected to reach $25.6 billion by 2027 (CAGR 32.1%), with RAG tools driving enterprise adoption.
