37 posts tagged with "iApp Technology"

On 22 September 2026, NVIDIA published its round-up of NVIDIA AI Day Singapore (Raffles City Convention Centre, 22–23 September). Under the heading "Southeast Asia Technology Leaders Build With NVIDIA Nemotron Open Models for Region-Specialized AI", Thailand is represented by iApp Technology, the Big Data Institute and OpenThai 2.0 Legal, our open-source Thai legal model.

Tonight we are releasing OpenThai-SystemOne, an open-source Thai and English System One decision model: 0.8B parameters, Apache 2.0, weights and training recipe on Hugging Face and GitHub, and a free hosted API on api.iapp.co.th.

It does not write. It decides. Send it a state and typed questions; it returns a calibrated probability for every option of every question in one forward pass, with zero output tokens.

Model page: iapp.co.th/openmodels/openthai-systemone · Weights: huggingface.co/iapp/OpenThai-SystemOne · Code: github.com/iapp-technology/openthai-systemone · Try it: API playground

One day after launch, iApp Image Generation moves to version 1.1.0. The theme of this release is เพิ่มความเป็นไทยและความสมจริงเข้าไปอีก: more Thai, more realistic. Thai text now looks like part of the photograph rather than a label placed on top of it, the model knows Thai public figures by name, and you can hand it a reference image of your own.

The following is the official press release issued on 2 September 2026.

Bangkok, 2 September 2026 — iApp Technology today launched iApp Image Generation, the first AI image generation model built by a Thai team for the Thai language. Developed by the iApp Technology team, the service produces posters, shop signs, greeting cards, product labels, presentation slides and social-media graphics in which the Thai text appears exactly as the user typed it — every consonant, vowel and tone mark in place. It is available today to every iApp AI API account at a preview price of 1.5 IC per image, half the list price of 3 IC.

Dear Users,

We are pleased to announce the release of version 3.0 of our License Plate Recognition (LPR) API. This release replaces the vehicle make/model recognition engine with a new deep-learning classifier built specifically for the Thai car market — the largest accuracy improvement in the product's history.

What's new in version 3.0:

• Vehicle brand & model accuracy improved dramatically — brand accuracy 99.4% (up from 38.5%) and make+model 99.18%, measured on 853 real photos of today's Thai traffic. The previous engine was built for the market of its era — much of today's traffic consists of 2020–2026 models and EV brands that simply didn't exist in its catalog, which is exactly what version 3.0 fixes
• Supports the newest cars — the recognition catalog now covers 73 models across 17 brands in the current Thai market, including 2020–2026 models and Chinese EV brands such as BYD, MG, GWM and Neta that previous versions could not identify
• New: fuel type & EV detection — every identified vehicle now reports its fuel type (EV / Hybrid / Petrol / Diesel), enabling EV analytics for parking and smart-city use cases
• New: confidence scores — make/model confidence and an independent logo-brand verification are included in every response
• New: neighbor-country plates — Malaysia (production), Myanmar (beta) and Laos (detection-only)
• Reliable on gate cameras — brand recognition stays correct and consistent even on tight close-up framing from parking and village entrance cameras

With OpenThai 2.0 reaching thousands of developers this week, we would like to make one thing clear for everyone building on it: OpenThai — the name and the logo — is a registered trademark of iApp Technology Co., Ltd., registered with Thailand's Department of Intellectual Property under registration no. 251122938.

This is a housekeeping note, not a policy change. The models are open and stay open. This post simply puts the ownership on the record and explains how the name may be used.

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.

The free period of the hosted OpenThai 2.0 Legal API was scheduled to end on 24 August 2026. We are extending it: the API remains free through 30 September 2026 with any free iApp API key.

In its first month the endpoint served nearly 2,000 requests from 88 registered developers — lawyers, legal-tech builders and researchers asking real Thai legal questions and getting answers grounded in the current statute text. The extra five weeks give everyone still evaluating the model time to finish their integration on the free tier.

Dreamina Seedance 2.5 is now available through the iApp platform, sitting alongside Seedance 2.0 on the same endpoint and the same API key. BytePlus released it on 7 August 2026; it is live on iApp today.

The headline change is length. Seedance 2.0 renders 5-second clips; 2.5 renders up to 30 seconds — long enough for a complete product spot or a scene with a beginning, middle, and end, rather than a loop you have to stitch. Motion is noticeably steadier over that longer window, and the model holds a subject's identity across shots far better than 2.0 did.