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What Are AI Models and Machine Learning? And How Does Low-Code Help?
An AI Model is a programme that has been trained to recognise patterns in large amounts of data —and then apply those patterns to make decisions or predictions when it encounters new data.
To put it simply: if you want a system to automatically approve or decline loan applications, you need an AI Model trained on hundreds of thousands of historical applications — learning which customer profiles carry high or low risk.
AI Models come in several types depending on the task:
Classification Model: Used to determine whether an email is spam, or whether a product image matches a specific category.
Predictive Model: Used to forecast next month’s sales figures, or to identify which customers are likely to stop using a service.
Large Language Model (LLM) — includingGenerative AI: Used to generate text, summarise documents, answer questions, or translate between languages.
Furthermore, all of these operate on the same fundamental principle: learn from historical data, then apply that learning to new situations.
How Does Machine Learning Work? the task:
Machine Learning is the process that enables computers to learn without being explicitly programmed for every scenario. In practice, it follows three main stages:
First: Feed the data
Developers supply the system with large volumes of data — for example, five years of transaction history, or 100,000 product images.
Next: Train the model
The system analyses the data repeatedly, searching for patterns that indicate what the correct output should be. Think of it like a child learning from repeated examples until the recognition becomes automatic.
Finally: Test and deploy
Once training is complete, the model is tested against data it has never seen before. If the results are accurate enough, it is deployed into production.
One critical point: a good model requires good data. If the training data is incomplete or biased, the model will make flawed decisions as a result. Consequently, many Thai enterprises have not yet been able to use AI effectively —because the data within their organisations is not yet ready.
How Are Thai Enterprises Using AI in 2026?
From our experience working with organisations across multiple industries in Thailand, AI adoption typically falls into three levels:
- Level One: Using off-the-shelf AI
Many organisations start with existing AI tools — for example, ChatGPT for drafting
documents or Google Translate for language conversion. This level is fast to start but offers limited customisation.
- The next step: Embedding AI into existing systems
More advanced organisations connect AI to their existing workflows — for example, adding a document reading and summarisation capability to their contract review process, or using AI to pre-screen loan applications before they reach an officer for a decision.
- The highest level: Building custom AI Applications
Organisations that need AI tailored precisely to their business requirements must build their own AI Applications. This level demands the most time and resources.
However, the most common challenge in Thai enterprises is wanting the results of level three without having a dedicated AI development team — and without the time to wait for a build-from-scratch project.
How Does Low-Code Like Mendix Help Build AI Applications Faster?
1. Maia AI — An AI Assistant Built Into the Development Environment
Mendix Maia is an AI assistant embedded directly in the development environment. It helps generate workflows, write business logic, and suggest solutions — enabling IT teams to build applications faster without manually coding every component.
2. Connect to Leading AI Services Immediately
Mendix connects directly to leading AI services through pre-built connectors — including Azure OpenAI, AWS Bedrock, and Google Cloud AI. As a result, organisations do not need to build their own AI models. Instead, they can embed existing models into their enterprise systems immediately throughMendix AI-Augmented Applications.
3. Enterprise-Grade Control
A Real-World Example from Thailand
From our work with organisations in Thailand’s financial sector, we have seen a consistent pattern:
The problem: Staff were required to read and summarise 30–50 contract documents per day on average. Each document took 15–20 minutes to process,
and the risk of missing critical details was high.
The solution using Low-Code and AI:
The team built a system on Mendix connected to Azure OpenAI. The system reads uploaded documents, summarises key points, and flags any concerning conditions automatically.
Staff still make the final decision — but the time per document decreased significantly.
What made it fast:
No AI model needed to be built from scratch. The team used pre-built connectors from Mendix Marketplace and built the user interface on Low-Code — making the time
from design to deployment significantly shorter than traditional development. For more on this type of solution, see TBN’s Contract Management solution.
Frequently Asked Questions
Q: How much data does an organisation need
before it can start using AI?
A: It depends on the type of AI. If you use an off-the-shelf model such as Azure OpenAI
or Google Cloud AI, you do not need to train a model yourself. However, if you need a highly specialised model, you will need sufficient clean and structured data within your organisation.
Q: Will AI replace employees in Thai enterprises?
A: No — it augments them. AI handles repetitive tasks faster and more accurately
than people. However, important decisions, communication, and relationship-building still require human judgement. Therefore, the organisations that use AI most effectively
are those that know which tasks to assign to AI and which to keep with people.
Q: How is Low-Code with AI different from hiring a Data Science team?
A: Hiring a Data Science team takes time, requires significant investment, and is best suited to organisations that need
highly specialised models. In contrast, Low-Code platforms like Mendix are designed
for organisations that want to embed existing AI capabilities into real business workflows — quickly and with full control.Talk to TBN to assess which approach is right for your organisation.
