Documentation Index
Fetch the complete documentation index at: https://docs.omnifact.ai/llms.txt
Use this file to discover all available pages before exploring further.
When you’re working in an Omnifact Space with uploaded documents, you’re using one of AI’s most powerful capabilities: getting information from your own documents. This means AI can search through your documents, find relevant information, and use it to provide accurate, grounded responses.
Think of it like having a research assistant who has read all your company documents and can instantly find and cite the exact information you need for any question.
Understanding Document Search in Omnifact Spaces
What Happens Behind the Scenes
When you ask a question in a Space with uploaded documents:
- Your question is analyzed - AI understands what you’re looking for
- Documents are searched - The system finds relevant sections from your uploaded files
- Information is found - Key passages are pulled from the most relevant documents
- Response is created - AI creates an answer based on the found information
- Sources are provided - You see which documents were used
Why This is Powerful
- Accuracy: Answers are based on your actual documents, not AI’s general knowledge
- Current Information: Information is as up-to-date as your uploaded documents
- Specific to You: Responses are tailored to your organization’s context
- Verifiable: You can check answers by looking at the source documents
The Art of Knowledge Base Prompting
Basic Principles
Instead of asking broad questions, focus on specific information you need from your documents.
❌ Vague: “What’s our policy on vacation?”
✅ Specific: “What is the maximum number of consecutive vacation days an employee can take according to our HR policy?”
❌ Vague: “Tell me about the project”
✅ Specific: “What are the key milestones and deadlines outlined in the Project Alpha documentation?“
2. Use Document-Aware Language
Ask as if the answer is in your documents:
✅ “According to our quarterly report, which product lines grew most?”
✅ “From customer feedback, what are the top three feature requests?“
3. Request Evidence and Citations
Ask for sources in the answer:
✅ “What are our data retention requirements, and which policy document states them?”
✅ “List approved software vendors with the policy section for approval criteria.”
Creating Summaries from Multiple Sources
Create a comprehensive executive summary of our Q3 performance by combining information from:
- The quarterly financial report
- Customer satisfaction survey results
- Employee engagement data
- Market analysis documentation
Structure the summary with: Financial Performance, Customer Insights, Employee Satisfaction, Market Position, and Key Recommendations.
Building Comparison Tables
Create a comparison table of our three main product lines using information from our product specification documents. Include features, target markets, pricing models, and competitive advantages for each product.
Extracting Action Items and Decisions
Review all meeting minutes from the leadership team for October and extract:
- All action items with assigned owners and deadlines
- Strategic decisions made and their rationale
- Unresolved issues that need follow-up
Present this as a consolidated action tracker.
Basic Troubleshooting
Solutions:
- Rephrase your question using different terminology
- Break down complex questions into simpler parts
- Check if the information actually exists in your uploaded documents
- Try broader search terms first, then narrow down
Example Troubleshooting Sequence:
// First attempt - too specific
"What is our customer churn rate for the enterprise segment in Q3?"
// If not found, try broader
"What customer retention metrics are reported in our Q3 documents?"
// Then narrow down based on what's available
"Based on the retention data you found, can you calculate or identify metrics specifically for enterprise customers?"
Verify and Cross-Reference
You mentioned that our customer satisfaction score is 85%. Can you show me exactly where this number appears in our documents and confirm it's referring to overall satisfaction rather than a specific metric?
Request Multiple Sources
Find all references to our employee turnover rates in our HR documents. If there are different numbers, explain the differences and which source is most recent.
When Responses Are Too General
Ask for Specific Details
You mentioned we have a "comprehensive training program." Can you provide the specific details from our HR documentation about training requirements, duration, and certification processes?
Instead of summarizing our incident response process, please provide the exact step-by-step procedure as outlined in our IT security documentation.
Best Practices for Knowledge Base Prompting
1. Start Broad, Then Narrow
Begin with general questions to understand what information is available, then drill down:
// First: Explore what's available
"What topics are covered in our customer service documentation?"
// Then: Get specific information
"Based on that overview, what are the specific response time requirements for different types of customer inquiries?"
2. Use Follow-Up Questions Effectively
Build on previous responses to dig deeper:
// Initial question
"What are our main revenue streams according to the financial reports?"
// Follow-up based on response
"For the subscription revenue you mentioned, what are the growth trends and customer acquisition costs over the past year?"
Create a structured breakdown of our product development process from the engineering documentation:
**Phase 1: Planning**
- Key activities:
- Required approvals:
- Typical duration:
**Phase 2: Development**
- Key activities:
- Quality checkpoints:
- Typical duration:
[Continue for all phases]
Getting Started
Working with Knowledge Base documents transforms your organization’s information into an intelligent, searchable resource. Start with simple, specific questions about your uploaded documents, then build complexity as you get comfortable. Remember: precise prompts lead to precise answers.
