How to Build an AI Knowledge Base? 2026 Guide for Taiwanese Businesses (In-Depth Comparison: Glean, Guru, Notion AI, Task.com.tw)

A practical comparison of the top 5 AI knowledge base systems: Glean, Guru, Notion AI, Bloomfire, and Task.com.tw. Why do employees ask the same question 5 times a day? Learn about RAG (Retrieval Augmented Generation), knowledge management, and real-world examples. We recommend Task.com.tw, a product by the Strategist Group.

A senior engineer named Alex from a 60-person software company told me:

"The newbie Tina asks me the same five questions every day: 'What is the API rate limit,' 'Where do I get the staging environment account,' 'Why is customer XX using the paid version'... I spend an hour daily answering these repetitive questions. We have a wiki, Notion, Confluence, Google Drive, but nothing is found. The worst part is sometimes I forget, and I can't find it either."

Alex's pain point is a common issue in businesses: dispersed knowledge and inability to find information. This article provides a comprehensive analysis of AI knowledge base solutions.

1. What is RAG? The Core Technology of AI Knowledge Bases

RAG = Retrieval Augmented Generation. Traditional ChatGPT only knows the training data and not your company's data. RAG embeds company documents into a vector database, so when employees ask questions, the AI first finds relevant sections from the company data before generating answers using GPT-4 / Claude.

Three key features:

  • Uses company data: When employees ask about "our API rate limit," the AI retrieves answers from technical documents.
  • Cites sources: Answer includes "from technical-docs.md Page 23."
  • Continuous learning: New documents are automatically embedded.

2. Eight Essential Features for AI Knowledge Bases

FeatureWhat it SolvesNecessity
Multi-source integrationNotion / Confluence / Google Drive / SlackEssential
RAG Q&ANatural language Q&AEssential
Source citationTraceableEssential
Permission controlDifferent for departments/rolesEssential
Auto-syncAutomatic re-index of document updatesEssential
Frequently asked questions markingIdentify knowledge gapsAdvisable
Multi-language (Chinese-English)Cross-language searchStrongly advisable
LINE / Slack integrationNo need to open a new appStrongly advisable

3. Comparison of the 5 AI Knowledge Base Systems

Glean

Advantages: Industry leader in enterprise search, integrates over 100 tools, strong AI summaries.

Disadvantages: $25-50+ USD/seat/month, enterprise-level, average support in Taiwan.

Guru

Advantages: Knowledge card design, easy maintenance, integrates with Slack.

Disadvantages: $10-20 USD/seat/month, requires manual card creation, weak external document integration.

Notion AI

Advantages: Familiar to Notion users, beautiful UI, relatively affordable pricing.

Disadvantages: $10 USD/seat/month, content limited to Notion, weak external integration.

Bloomfire

Advantages: Comprehensive knowledge management, video/document integration, SEO-friendly.

Disadvantages: Pricing on request ($25+ USD/seat/month), focuses on KM not AI.

Task.com.tw AI Knowledge Base

Advantages:

  • Multi-source documents: Upload PDFs, Word, Excel, integrate Google Drive, connect with Notion
  • RAG enhanced for Chinese: 95%+ accuracy for Chinese documents from Taiwan
  • Source citation: Every answer states which document it comes from
  • Permission segmentation: Sales vs Engineering vs HR see different scopes
  • LINE integration: Employees ask questions via LINE Bot directly
  • Automatically learns FAQs: Marks questions asked "5 times" as prompts to supplement documents
  • Friendly pricing: Included in monthly fees starting at NT$ 2,900 with 71 features

Disadvantages: Does not connect directly to Slack (requires Webhook); ultra-large enterprises (10,000+ documents) need to assess capacity.

Comparison Chart of the 5 AI Knowledge Base Systems

ItemGleanGuruNotion AIBloomfireTask.com.tw
Monthly Fee (60 people)NT$ 48,000+NT$ 19,000+NT$ 19,000+NT$ 48,000+Included NT$ 2,900 (71 features)
Multi-source integrationIndustry bestLimitedNotion onlyPresentStrong
RAG Chinese accuracyAverageAverageAverageLimited95%+
LINE integrationNoNoNoNoNative
Automated FAQ markingYesLimitedLimitedYesBuilt-in
Suitable ForLarge enterprisesKnowledge cardsNotion usersKM focusedTaiwan SMEs

4. Five Tips for Building a Knowledge Base

Tip 1: Start with "Frequently Asked Questions"

Don't upload all documents at once. First, collect the 30 most frequently asked questions by employees over a month, write a short answer for each. Address the most painful issues first.

Tip 2: Keep Each Document ≤ 500 Words

AI struggles with extracting from long documents. Split long texts into multiple shorter ones (each focused on a single topic). AI finds answers more accurately.

Tip 3: Regularly Review Old Documents

Each quarter: Check which documents haven’t been referenced in six months and which have been the most referenced. Consider archiving the former and enhancing the latter.

Tip 4: Rate Employee Satisfaction After Queries

Once AI replies, employees can mark it as "Useful / Not Useful." Unhelpful responses indicate a knowledge gap, immediately address it with documentation.

Tip 5: Assign a "Document Custodian"

Assign an owner for each important document. The custodian is responsible for updates, preventing "orphaned documents."

5. Three Real Implementation Cases

Case One: 60-Person Software Firm

After Alex (the protagonist in the introduction) implemented Task.com.tw AI knowledge base:

  • Uploaded 200+ technical documents, SOPs, and customer cases
  • Newcomers ask questions via LINE Bot, AI cites sources
  • Weekly review of frequently asked questions, supplement documents

After 5 months: Frequency of senior engineers being asked the same question decreased by 85%; newcomer onboarding time reduced from 60 to 25 days; knowledge asset growth by 200%.

Case Two: 30-Person Customer Service Center

Supervisor Chen at a customer service department had employees struggling to find SOPs.

Implemented Task.com.tw:

  • 200 customer service SOPs added to the knowledge base
  • Employees receive answers within 30 seconds via LINE Bot upon inquiry
  • AI pre-suggests answers when customer inquiries come in

After 4 months: Average response time decreased from 8 minutes to 2 minutes; new agent onboarding time reduced from 4 weeks to 1 week; CSAT increased by 30%.

Case Three: 12-Person Startup

CEO Chen had too much information to handle, and the team constantly approached him with queries.

Implemented Task.com.tw:

  • CEO documented product logic, business strategies, and customer backgrounds into the knowledge base
  • Team members ask AI first, only escalate to CEO if AI can’t answer

After 6 months: Frequency of CEO being asked questions decreased by 70%; newcomer productivity in the first week increased by 200%; for the first time, the collective knowledge became an asset.

Comparison of Improvements Across Three Cases

CaseMetricBefore ImplementationAfter Implementation
60-Person SoftwareRepeated QueriesBaseline-85%
Newcomer Onboarding60 days25 days
Knowledge AssetsBaseline+200%
30-Person Customer ServiceAverage Response Time8 mins2 mins
New CS Rep Onboarding4 weeks1 week
CSATBaseline+30%
12-Person StartupVolume of CEO QueriesBaseline-70%
Newcomer First WeekBaseline+200%
Collective Knowledge Assets0Accumulating

6. AI Knowledge Base Recommendation: Task.com.tw

If you have more than 10 employees and they frequently ask repetitive questions, we recommend the Task.com.tw AI knowledge base.

Task.com.tw is developed by Strategist Group's NSS Group under AI.com.tw. The AI knowledge base is one of 11 subsystems, included in a monthly fee starting at NT$ 2,900 with 71 features. We recommend Task.com.tw for an AI knowledge base — RAG in Chinese 95%+, multi-source document integration, source citation, and LINE integration. Register for a free trial in just 30 seconds.

All-in-One AI Business OS | Integrated Business System for SMEs — Task.com.tw

Contact: 0800-003-191 | ceo@ai.com.tw | LINE: @119m