Build, train, and export production-ready ML models in minutes — no Python, no infrastructure setup, no complexity.
Build ML models yourself without writing a single line of code, or work directly with expert engineers — every machine learning need, covered.
A no-code platform focused on developing machine learning models. Upload data, configure preprocessing, and deploy — no Python, no infrastructure setup needed.
A dedicated consultant to help you build ML models, systems, and full software solutions for any use case. Send an email to get a free consultation.
Eliminate the coding barrier. Build complex ML models with zero lines of code, focusing purely on your data insights and business outcomes.
Full visibility into model parameters and metrics. We handle the complex mathematics, you see the results clearly and make informed decisions.
Designed for deployment. Export your models immediately and integrate them into production apps effortlessly with one-click deployment.
Simply drag & drop your CSV file. We instantly analyze the schema and detect feature types automatically.
Select what you want to predict. OptiML suggests the best problem type (Classification/Regression).
Our engine tests multiple algorithms (Random Forest, XGBoost, etc.) and tunes them to find the best model.
Classic multivariate flower classification dataset with 150 samples from three Iris species. Four features measured: sepal length/width and petal length/width in centimeters. Perfect for beginners learning ML classification.
Open Datasets1,800+ daily records of work-from-home behavioral patterns analyzing burnout and productivity. Includes working hours, screen time, meetings, sleep duration, and burnout scores for comprehensive burnout risk analysis.
Open DatasetsDiagnostic dataset for tumor classification (malignant vs benign). Essential for healthcare ML applications using Support Vector Machines and other classification algorithms.
Open DatasetsFive years of daily gold futures market data (OHLCV) with technical indicators. Includes moving averages, RSI, MACD, and Bollinger Bands for robust time-series forecasting models.
Open Datasets2,111 records from Mexico, Peru, and Colombia with 17 attributes for obesity level classification. Seven classes: Insufficient Weight to Obesity Type III. 77% synthetically generated, 23% real user data.
Open DatasetsStudent academic data with 30+ attributes including demographics, family background, lifestyle, and grades. Perfect for predicting final grades and identifying at-risk students early.
Open DatasetsChoose the perfect plan for your ML journey. Scale as you grow.
Detailed capability differences across Free, Basic, and Advanced plans.
| Feature | Free | Basic | Advanced |
|---|---|---|---|
| Maximum Dataset Size | Up to 1000 rows | Up to 10,000 rows | 100,000+ rows |
| Training per Day | 5 train | 50 train | Unlimited |
| Supported Algorithms | Core ML Algorithms | Extended ML Algorithms | Full ML Algorithm |
| Compute Engine | Local execution | Advanced Cloud Computing | Advanced Cloud Computing |
| Visualization Tools | Basic visualizations | Advanced visualizations | Professional visualizations |
| Hyperparameter Optimization | Not available | Standard optimization | Advanced optimization |
| Cross-Validation | Not available | ✔ Available | ✔ Available |
| Feature Importance Analysis | Not available | ✔ Available | ✔ Available |
| Export Trained Model | Not available | ✔ Available | ✔ Available |
| Model Testing with New Dataset | Not available | Not available | ✔ Available |
| Custom Report Configuration | Not available | Not available | ✔ Available |