What is the new hierarchical structure of QommonsAI?

The new hierarchical structure allows for up to five levels of folder management, enabling you to organize internal documents in the same way as on an existing file server, and directly utilize it for AI search (RAG).

Is data reclassification necessary during implementation?

No, it is not necessary. The 'Easy RAG' feature allows you to upload while maintaining your existing folder structure, and the AI automatically organizes the data to immediately improve answer accuracy.

Which local governments is this best suited for?

This is ideal for local governments where documents are scattered by department, and despite the introduction of generative AI, internal data references are not functioning effectively.

AI News NQ Analysis

QommonsAI Equips Private Knowledge with a 'New Hierarchical Structure.' Systematizing Internal Government Documents with Up to 5 Levels of Folder Management and 3-Tier Role Permissions to Radically Change AI Response Accuracy

NQ Score 77/100

N1 Content Completeness 8

AI Summary (NQ-processed)

Polimill Inc. has launched a 'New Hierarchical Structure' for its government-focused generative AI 'QommonsAI.' It solves the data organization challenges in municipalities by enabling instant AI RAG deployment directly from existing folder structures without manual reclassification.

AI Analysis

Frequently Asked Questions

Q: What is the new hierarchical structure of QommonsAI?: A: The new hierarchical structure allows for up to five levels of folder management, enabling you to organize internal documents in the same way as on an existing file server, and directly utilize it for AI search (RAG).
Q: Is data reclassification necessary during implementation?: A: No, it is not necessary. The 'Easy RAG' feature allows you to upload while maintaining your existing folder structure, and the AI automatically organizes the data to immediately improve answer accuracy.
Q: Which local governments is this best suited for?: A: This is ideal for local governments where documents are scattered by department, and despite the introduction of generative AI, internal data references are not functioning effectively.