2 posts tagged with "RAG"

Today we are launching Chinda 3, the third generation of our enterprise AI knowledge platform — built for organizations whose documents are too sensitive to send away and too complex for keyword search. Chinda 3 reads your company documents the way a human expert does, answers in Thai or English with page-level citations, and runs wherever your data is allowed to live: our cloud, your servers, or a fully air-gapped room.

👉 See it in action and explore plans at iapp.co.th/products/chinda3

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.