Start with real data
Upload CSV or Excel files, inspect schema, choose the prediction column, and normalize data in one workflow.
HAutoML -
Distributed AutoML
Made Simple
Train, optimize, and deploy machine learning models through an intuitive no-code platform.
No-codeDistributedAuto OptimizationAI-powered
Accuracy94.7%
Training time12.4s
Models tested128
HAutoML System
OptiVisionLab Research Laboratory
HAutoML stands for HYPER-PROCESSOR AUTOMATED MACHINE LEARNING. An open platform researched and developed by OptiVisionLab, delivering high-performance end-to-end distributed AutoML capabilities.
The system focuses on low-code and no-code workflows, helping users easily build, evaluate, and deploy machine learning models.
⚡ Low-code & No-code🔬 OptiVisionLab Research🤖 Distributed AutoML Automation
Realize the Distributed AutoML Pipeline
From raw dataset to production-deployed models on an end-to-end distributed architecture.
LIVEFPS: 60.0
0:00.00
Tải dữ liệu • ENB2012_data.xlsx01
00:00 – 00:08
Upload Dataset
Navigate to My Datasets, upload the tabular dataset file (ENB2012_data.xlsx), and confirm save.
00:08 – 00:18
Select Target & Features
Choose Regression task, configure the Target variable (Y1) and input Features (X1 to X8), then start training.
00:18 – 00:27
Automated Distributed Training
The system automatically executes pipelines, tunes hyperparameters, and benchmarks algorithms on visual leaderboards.
00:27 – 00:31
Deploy & Activate Model
Select the best champion model to deploy and click Activate to obtain your production API endpoint and code snippet.
Thousands of AI engineers & researchers rely on HAutoML in their domain.
Proud winner of prestigious awards in Student Scientific Research and National Innovative Startup Competitions (SV.STARTUP). Empowering students, researchers, and AI engineers to accelerate end-to-end machine learning workflows.
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1st Prize
1st Prize Student Scientific Research 2025 - 2026
17th Student Scientific Research Conference & Award - HaUI
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2nd Prize
2nd Prize Student Innovative Startup Ideas HaUI - Startup Mindset 2025
HaUI - Startup Mindset 2025 Competition Finals
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National
Consolation Prize - 8th National Student Startup Festival
SV.STARTUP - National Innovation Startup Festival (MOET & MOST)
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Promising
Promising Award - NextGen Student Innovative Startup Challenge
NextGen Entrepreneurship Challenge - HaUI
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Innovation
Consolation Prize - HaUI Innovation Day
HaUI Innovation Day 2025 – Pitching Competition
An AutoML platform for research, learning, and fast model deployment experiments.
8+
algorithms
4
sample data sources
1-click
test/deploy
From dataset to deployed model in one flow
The new homepage highlights what HAutoML does best: turning machine learning pipelines into observable, stateful, and adjustable steps.
Track pipelines visually
The progress map shows data reading, preprocessing, hyperparameter optimization, feature generation, and model evaluation.
Deploy the winning model
Leaderboard, insight panel, and test upload help you pick the champion model and use it faster.
Choose a template, tune parameters, run the pipeline
Marketplace is the starting point for common tasks: classification, regression, churn prediction, and model testing.
Explore marketplace1
Glass classification
table -> preprocess -> KNN
2
Credit approval
cleaning -> ensemble -> deploy
3
Customer churn
feature engineering -> XGBoost
An automation platform built for machine learning
Users can quickly understand model state: reading data, optimizing parameters, which pipeline performs best, and how to test it.