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• Remove outdated info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• Update outdated info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

1. **Quality over quantity** - Accurate content matters more than volume

2. **Structure helps** - Organized content = better retrieval

3. **Be specific** - Detailed content = detailed answers

4. **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.

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