Question 1

What is UniDrive and how is it different from traditional file managers?

Accepted Answer

UniDrive is an AI-native knowledge studio that sits on top of your real files—not another cloud silo. Unlike traditional file managers that rely on folder hierarchies and filename searches, UniDrive uses RAG (Retrieval-Augmented Generation) technology with semantic search to understand the meaning and context of your documents. AI agents automatically organize, tag, and retrieve information based on what you're actually looking for, not just matching keywords.

Question 2

What's the difference between AI agents and chatbots?

Accepted Answer

AI agents in UniDrive are autonomous systems that take actions, make decisions, and execute complex workflows on your behalf. Unlike chatbots that simply respond to queries, our AI agents can organize files, create tag hierarchies, analyze document relationships, and proactively suggest improvements to your knowledge base structure. They learn from your usage patterns and continuously optimize your workspace.

Question 3

What file formats does UniDrive support?

Accepted Answer

UniDrive supports all major file formats including documents (PDF, DOCX, TXT, MD), spreadsheets (XLSX, CSV), presentations (PPTX), images (PNG, JPG, SVG), code files (all programming languages), and our .uni format for rich collaborative documents. The RAG search engine extracts and understands content from all these formats, making everything searchable by meaning.

Question 4

How does RAG semantic search work?

Accepted Answer

RAG (Retrieval-Augmented Generation) combines semantic understanding with intelligent retrieval. UniDrive converts your queries and documents into vector embeddings that capture meaning, not just words. This lets you find information by describing concepts, asking natural language questions, or searching for ideas that aren't explicitly mentioned. The system understands context, relationships, and intent.

Question 5

How does automatic tagging work?

Accepted Answer

UniDrive's automatic tagging is powered by our LOGOS engine, a cutting-edge AI framework developed by researchers from UC San Diego and other top institutions. LOGOS replicates the expert-level thought process of qualitative research, automatically analyzing your documents to generate intelligent tag hierarchies. It understands semantic connections, clusters related concepts, and builds logical tag structures that reveal hidden patterns in your content. Learn more about LOGOS in our blog post.

Question 6

What's the difference between knowledge management and document management?

Accepted Answer

Document management focuses on storing, organizing, and retrieving files through traditional folder structures and basic search. Knowledge management goes beyond file storage to understand content relationships, automatically organize information, and create intelligent connections between documents. UniDrive combines both with universal tags, semantic search, and AI agents that substantially reduce manual organization effort.

Question 7

How does UniDrive differ from other knowledge management tools?

Accepted Answer

Traditional knowledge management tools rely on manual organization—folder structures, database setups, manual link creation. UniDrive introduces a file-native AI knowledge layer that continuously manages your knowledge ecosystem. Our AI agents automatically create universal tag hierarchies, keep your knowledge base self-organizing, and proactively optimize information relationships as your work evolves.

Question 8

Is my data secure? Where is it stored?

Accepted Answer

Your data security is our top priority. UniDrive offers both cloud and local storage options. All data is encrypted in transit and at rest. You have full control over where files are stored—choose between our secure cloud infrastructure or completely local-only mode for maximum privacy. We never train AI models on your private data.

Question 9

Do you train AI models on my data?

Accepted Answer

No. We never train AI models on your private content. All vector embeddings are generated using privacy-preserving techniques. Your documents remain yours. When using cloud features, data is processed ephemerally for search and organization, not stored for model training.

Question 10

What's the pricing model?

Accepted Answer

UniDrive offers flexible credit-based pricing starting with a free Bronze tier (1,500 credits). Credits power AI operations like semantic search, auto-tagging, and document analysis. Paid tiers range from $4.99/month (Silver - 6,250 credits) to $49.99/month (Diamond - 62,500 credits). New users get the first month completely free with unlimited access.

Question 11

What can I do with credits?

Accepted Answer

Credits power all AI features in UniDrive. A typical semantic search uses about 50 credits. Auto-tagging a document uses 20-100 credits depending on length. AI chat interactions vary based on context size. The free Bronze tier gives you approximately 30 searches per month—enough to experience core features before upgrading.

Question 12

Is there a free trial?

Accepted Answer

Yes! New users get the first month completely free with unlimited access to all features. After that, you can continue with our free Bronze tier (1,500 credits/month) or upgrade to a paid plan for more capacity. No credit card required to start.

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