Table of Contents
How to Train AI on Your Own Data
Training AI on your data creates assistants that actually know your information.
What "Training" Means
When we say "train AI on your data," we mean:
- Giving AI access to your information
- Creating searchable knowledge
- Enabling accurate responses
This is different from model fine-tuning (which requires ML expertise).
What Data Can You Use?
Documents
- PDFs
- Word documents (.docx)
- Text files (.txt)
- Markdown (.md)
Web Content
- Website pages
- Help center articles
- Blog posts
Structured Data
- FAQ pairs
- Q&A databases
- CSV files
The Training Process
1. Prepare Your Content
Best practices:
- Organize by topic
- Remove outdated info
- Include comprehensive coverage
- Write clearly
2. Upload to Assisters
- Navigate to your assistant
- Click "Knowledge Base"
- Upload files or add URLs
- Wait for processing
3. Processing Happens Automatically
We handle:
- Text extraction
- Chunking into sections
- Vector embedding
- Index optimization
4. Verification
Test your assistant:
- Ask questions from your docs
- Check answer accuracy
- Identify gaps
5. Iterate
Add more content as needed:
- Fill knowledge gaps
- Update outdated info
- Expand coverage
Tips for Better Training
- Quality over quantity - Accurate content matters more than volume
- Structure helps - Organized content = better retrieval
- Be specific - Detailed content = detailed answers
- Update regularly - Keep knowledge current
Common Issues
AI doesn't know something it should:
- Check if content was uploaded
- Look for processing errors
- Add more explicit content
AI gives wrong answers:
- Review source content for accuracy
- Check for contradicting information
- Update incorrect content
Your data, your AI, your control.