Wiki Search

Enterprise AI Knowledge Base

Connect your team to internal data using semantic AI search indices.

Solution Overview

We build private company search engines. By saving internal guides, training manuals, and policies as vector embeddings, staff can query corporate knowledge directly on chat panels.

We deploy RAG system architectures. We chunk company wiki files, index them inside vector tables, and configure chat dashboards for query responses.

Common Friction Points

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Staff losing hours search folders for specific policies or forms

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Slow onboarding times for new hires needing operational guidelines

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Knowledge loss when senior staff leave the organization

Core Benefits

  • check_circleInstant lookup of answers from thousands of corporate PDFs
  • check_circleShorter onboarding times for new hires
  • check_circlePreservation of institutional business guidelines

Recommended Technologies

LangChainPineconeNext.jsPythonFastAPIGoogle Drive API

Key System Features

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Feature 01

Automatic document import from Google Drive or local folders

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Feature 02

Web chat panel with source citation links

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Feature 03

Admin control panel to review and update indexes

FAQs

Answers to common solution queries

Can we control document permissions?expand_more

Yes. We configure user role permissions (RBAC) so employees can only retrieve answers from documents their profiles are allowed to see.

How do we add new files to the index?expand_more

We link folders to automated ingestion scripts. Saving a new PDF inside Google Drive syncs it to the vector database in minutes.