5 posts tagged with "Thai Language AI"

Today, together with the Artificial Intelligence Entrepreneur Association of Thailand (AIEAT), we are releasing OpenThai 2.0 — an open-source Thai vision-language model, 27B parameters, Apache 2.0, weights free on Hugging Face.

One month ago we released OpenThai 2.0 Legal, a specialist that knows Thai law by heart. OpenThai 2.0 is its generalist sibling, and the bigger release of the two: a single model that reads Thai documents and handwriting at specialist level, answers Thai knowledge questions in natural Thai, and calls tools reliably enough to run agents — while keeping its base model's general intelligence.

Model page: iapp.co.th/openmodels/openthai2p0 · Weights: huggingface.co/iapp/openthai2.0-qwen3.8-27b · Try it free, no install: chinda3.iapp.co.th

The following is the official press release issued on 26 August 2026.

Bangkok, 26 August 2026 — iApp Technology today released OpenThai 2.0 Legal, an open-weight large language model purpose-built for Thai law, and made its full weights freely available on Hugging Face. Built by Thais for Thailand, the model is designed for lawyers, in-house counsel, compliance teams, legal-tech builders and public agencies that need reliable, source-grounded answers on Thai statutes and case law.

iApp Any Documents OCR can now read six more Thai document types, and they are live on production today. Every one returns structured JSON with a per-field confidence score, at 1 IC per page.

Docs: Thai Document OCR · Pricing: iapp.co.th/pricing

Today we are releasing OpenThai 2.0 Legal, an open-weight large language model purpose-built for Thai law — and we are giving away the full weights on Hugging Face. It is built by Thais, for Thailand: for lawyers, in-house counsel, compliance teams, legal-tech builders and public agencies that need reliable, source-grounded answers on Thai statutes and case law.

Model page: iapp.co.th/openmodels/openthai2p0-legal · Weights: huggingface.co/iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b

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.