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RAG vs Fine-Tuning: When to Use Each Approach for Thai Language AI

· 16 min read
Kobkrit Viriyayudhakorn
CEO @ iApp Technology

By Dr. Kobkrit Viriyayudhakorn, CEO & Founder, iApp Technology

One of the most common questions we hear from Thai AI engineers and technical teams is: "Should I use RAG or fine-tuning for my Thai language application?" It's a critical question that directly impacts development costs, performance, maintenance complexity, and long-term scalability.

The answer, as with most engineering decisions, is: it depends. But understanding when to use each approach—and increasingly, how to combine them—can mean the difference between a successful AI deployment and an expensive failure.

This article provides a comprehensive technical comparison of Retrieval-Augmented Generation (RAG) and fine-tuning specifically for Thai language applications, drawing from our experience at iApp Technology deploying both approaches across hundreds of Thai enterprises.