Glossary
Fine-Tuning
Definition
Fine-tuning is further training a base AI model on your own domain data so it performs better on your specific tasks, tone, and terminology.
Last updated
Key points
- Changes how the model behaves; RAG changes what it knows — they're often combined.
- A small model fine-tuned for your domain can outperform a large general one.
- Builds a proprietary asset competitors can't easily replicate.
Quick answer
Fine-Tuning — common question
If your need is current, citable knowledge, RAG is usually enough. If you need consistent domain behavior, format, or specialized performance, fine-tuning helps — and the two work well together.
From concept to working product.
We build these ideas into real systems you own. Tell us what you're trying to do.