No-Code ML Models with API Integration

Machine Learning for Tech Companies

Build machine learning models from your data without coding or hiring data scientists. Train models automatically and connect them to your applications through simple API endpoints.

Get Started
API Request Example
curl -X POST https://api.mlclever.com/predict \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "context": {
      "heart_rate": 72,
      "blood_pressure": "120/80",
      "activity_level": "moderate"
    }
}'

Technical Specifications

Platform Capabilities

Key features and requirements for implementing machine learning in your tech stack.

  • Measurable

    Model Accuracy

    Track performance metrics for all predictive models.

  • Cloud-Based

    System Requirements

    No specialized hardware or infrastructure needed.

  • Flexible

    Data Handling

    Process structured data from various sources.

  • Straightforward

    Implementation

    Deploy models through API without complex DevOps.

Core Functionality

Platform Features

MLClever provides all the tools needed to build, deploy, and integrate machine learning models without specialized expertise.

AutoML

Automated Machine Learning

Upload data and automatically build optimized prediction models without ML expertise.

One-Click AutoML

One-Click AutoML

Create reusable ML workflows that can be retrained with new sales and inventory data.

Model Training

Model Training & Deployment

Train models on your data and deploy them with one click for application integration.

Predictions

API Prediction Endpoints

Connect trained models to your applications with RESTful API endpoints.

AI Dashboards

Interactive Dashboards

Create visualizations of your data and model performance with drag-and-drop components.

Preprocessing

Feature Importance Analysis

Understand which variables most impact your model's predictions.

ML for Technology Companies

Machine Learning Without Data Science Teams

Build predictive models directly from your existing data. MLClever handles the complex parts of machine learning so your development team can focus on integration and application development rather than model creation.
View Features
Technology Integration Dashboard

Platform Tools

Key Components

Essential tools for building and deploying machine learning solutions without specialized data science expertise.

AutoML ConfigurationBASICMEDIUMADVANCEDBuild Pipeline

Interactive Dashboards

Create visualizations of your data and model results with ready-made components. Monitor model performance and share insights with stakeholders.

1

Prediction Interface

Test models with different input values before deployment. Understand how changing variables affects prediction outcomes for your specific use cases.

random_forest
95
completed
neural_network
87
running
gradient_boost
92
completed

AutoML Pipeline Tracking

Monitor the progress of model building from data preprocessing through training to deployment. Each step is visible and automatically optimized.

API Integration

Connect ML Models to Your Applications

Once your model is trained, integrate predictions into your applications with simple API calls. Send data to the prediction endpoint and receive results that can be used directly in your software, websites, or internal tools.
API Documentation
API Integration Diagram

End-to-End ML Process

From Data to Deployment

MLClever handles the complete machine learning workflow from data upload through model training to deployment and integration.

Boston Housing
Regression Model
90
Training Complete
Last updated: 2h ago
Model Training

Machine Learning Models

Train regression and classification models automatically based on your data. Models are evaluated and optimized without manual tuning.

Learn more

Make a Prediction

age
sex
chest pain type
resting bp
cholesterol
max heart rate

Prediction Result

0
0: 0%
1: 0%
Predictions

No-Code Predictions

Generate predictions through a simple interface or API calls. Input your variables and receive instant predictions for decision-making.

Learn more
AutoML (advanced) on heart_statlog
random_forest
Score: 95.38
Feature Importance
ST slope
chest pain
max heart
cholesterol
Prediction
0
Result
Target: target
Sample Input Data
age: 54, sex: 1, chest pain: 4...
AI Dashboards

Drag-and-Drop Dashboards

Create custom visualizations without coding. Select from charts, tables, and metrics to build interactive data dashboards.

Learn more
Data Preprocessing
1
Preprocess datasets, configure models, and initiate workflows
Documentation
ML Clever
Model Training
2
Train and evaluate machine learning models with automatic tuning
Documentation
ML Clever
AutoML
3
Streamline training with automated machine learning pipelines
Documentation
ML Clever
AutoML

Auto Machine Learning

Upload your data and let the system automatically build the best model for your prediction task.

Learn more

Data Visualization

Understand Your Model Results

Create dashboards that visualize your data and model predictions. Track performance metrics, monitor prediction accuracy, and share interactive reports with your team—all without writing code.
Dashboard Features
Data Visualization Dashboard

Integration Capabilities

Technical Features

Specific features designed to help technology companies implement machine learning in their products and workflows.

Model Performance Tracking

Monitor how your models perform over time with accuracy metrics and performance dashboards. Identify when models need retraining.

API Prediction Endpoints

Each trained model gets a dedicated API endpoint with authentication. Send data in JSON format and receive prediction results for integration.

Automated Model Selection

The platform tests multiple model types and configurations to find the best performer for your specific dataset and prediction task.

Development Impact

Implementation Metrics

How MLClever affects the development and deployment of machine learning capabilities in your applications.

  • API Integration

    RESTful

    Connect models to your applications via simple API calls.

  • Model Training

    Automated

    Build ML models without data science expertise.

  • Development Time

    Reduced

    Deploy ML solutions in days instead of months.