#The Best Low Code AI Platform in 2025: Build AI Models by Chat

📅 05.12.25 ⏱️ Read time: 8 min

Every business wants AI. Very few have the engineering team to build it. That gap is exactly what low code AI platforms are designed to close — giving teams the ability to train, deploy, and integrate custom AI models without a machine learning background or infrastructure expertise.

But not all low code AI platforms are equal. Some are great for connecting pre-built models to workflows. Others are focused on prompt engineering. And a few — like Aicuflow — go further: letting you train custom models on your own data, by chat.

Before evaluating specific tools, it helps to define what "low code AI" actually means. There are three distinct categories often lumped together:

1. Low code automation with AI features Tools like n8n, Make.com, and Zapier connect APIs and automate workflows. Some include AI steps (like calling an OpenAI endpoint) but don't train custom models. They are excellent for workflow automation but not for building proprietary AI.

2. Low code prompt engineering platforms Tools that help you build LLM-powered applications — chatbots, document processors, retrieval systems — without writing code. Valuable for NLP use cases but not for tabular data, image recognition, or custom regression models.

3. Low code custom model training platforms The most powerful category: platforms that let you bring your own data, train a custom model, evaluate it, and deploy it as an API — all without code. Aicuflow lives here.

The best low code AI platform for your use case depends on whether you need to automate (category 1), prompt (category 2), or train (category 3).

Low code and AI intersect in several ways. Understanding the spectrum helps you choose the right tool:

Most business AI needs live at the "Configure" and "Train" levels — where you need something more than a pre-built model but don't have the resources for a full MLOps setup.

When evaluating any low code AI platform, ask these questions:

A platform limited to LLMs won't help you if you need tabular classification, regression, or computer vision. Look for platforms that support the AI task types relevant to your use case.

Aicuflow supports: classification, regression, clustering, NLP, computer vision, recommendation systems, RAG pipelines, and more.

The best AI platforms make data loading trivial. Supported formats should include CSV, JSON, PDF, API connections, and cloud datasets. Configuration should be chat-based, not code-based.

Training should be configurable without writing Python. Hyperparameter selection, train/test splits, and algorithm selection should be guided by the platform, not left to you.

The goal of any AI model is to be usable. The platform should produce a REST API endpoint with documentation and code examples — automatically.

The best low code AI platforms are genuinely accessible to analysts, domain experts, and product managers — not just developers who happen to prefer visual tools.

Aicuflow is built around a single thesis: you should be able to build a complete AI pipeline by describing what you want in plain language.

Every project lives on a visual canvas. You add nodes (data source, processing, training, evaluation, deployment), connect them in sequence, and run the pipeline. The canvas is the project.

The AI assistant interprets natural language instructions and configures nodes on your behalf:

• "Add a Kaggle dataset about customer churn"
• "Configure a classification model"
• "Add visualizations that show feature importance"

This means you can build a complete ML pipeline without opening a settings panel once.

Model training is configured through the chat interface and a structured training node. Algorithm selection, hyperparameter ranges, and evaluation metrics are all handled by the platform based on your data type and goal.

Once training completes, you deploy with a single action. Aicuflow generates a REST API endpoint with:

• Authentication tokens
• Request/response schema
• Code examples in Python, JavaScript, and cURL

→ Explore the full platform → Learn how training works → Learn how deployment works

Teams use Aicuflow to build:

• Customer churn prediction models — trained on CRM data, deployed as an API that scores customers in real time
• Demand forecasting pipelines — connecting sales data, generating predictions, and surfacing results in dashboards
• Document classification systems — categorizing incoming PDFs, emails, or support tickets automatically
• Recommendation engines — suggesting products, content, or actions based on user behavior
• RAG (Retrieval-Augmented Generation) pipelines — grounding LLM responses in your proprietary knowledge base
• Fraud detection systems — scoring transactions against trained anomaly detection models

Aicuflow is the right platform if:

• You have real business data and want to extract value from it with AI
• You don't have a dedicated data science team — or your team is already at capacity
• You need custom models, not just pre-built AI APIs
• You want to own the output: a deployed API that you control
• You want to move from idea to production in days, not months

→ See pre-built templates to get started instantly