After spending months frustrated with "one-size-fits-all" AI assistants that either didn't know my data or leaked it to public models, I built Advantis AI - a platform that lets you create and customize multiple AI agents that work exclusively with your own information.
I started building this when I was consulting for a law firm that needed AI help but couldn't risk uploading sensitive client documents to public AI services. The available solutions either lacked customization or required serious coding skills.
What it does: Advantis lets you create multiple AI assistants, each with different "expertise" based on documents you upload. Your data stays private, and each agent draws knowledge only from sources you explicitly approve. You can:
-Create specialized agents for different departments/topics
-Upload proprietary documents for the agent to learn from
-Control OCR and data retention settings
-Define specific roles and capabilities for each agent
-Switch between agents in a clean conversation interface
The technical stack is React 19 frontend with Node.js/Express backend, Supabase for auth/database, and a custom implementation for document processing. I've tried to keep the free tier generous enough to actually be useful (1 agent, 10 queries/month, 5 documents).
You can try it without providing a credit card - you can activate the free tier immediately after signup, and you can upload actual documents to test how your own data works with it.
What makes this different from other RAG implementations is the multi-agent system and the focus on ease of use - you don't need prompt engineering experience or coding skills to create specialized agents.
Would love feedback, especially from people who've tried building/using their own RAG systems or are dealing with domain-specific knowledge challenges!
-Create specialized agents for different departments/topics -Upload proprietary documents for the agent to learn from -Control OCR and data retention settings -Define specific roles and capabilities for each agent -Switch between agents in a clean conversation interface
The technical stack is React 19 frontend with Node.js/Express backend, Supabase for auth/database, and a custom implementation for document processing. I've tried to keep the free tier generous enough to actually be useful (1 agent, 10 queries/month, 5 documents). You can try it without providing a credit card - you can activate the free tier immediately after signup, and you can upload actual documents to test how your own data works with it. What makes this different from other RAG implementations is the multi-agent system and the focus on ease of use - you don't need prompt engineering experience or coding skills to create specialized agents.
Would love feedback, especially from people who've tried building/using their own RAG systems or are dealing with domain-specific knowledge challenges!