Platform

Automatic Model Deployments

Models deploy automatically after training completes. Access them through the ML Clever platform or integrate via API for external applications without managing infrastructure.

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Model Deployment Options

Trained Model
No Code Interface

Visual deployment for non-technical users

API Integration

Programmatic access for developers

No Code Features:
  • Drag & Drop Interface
  • Pre-built Templates
API Features:
  • REST Endpoints
  • Custom Integration

Infrastructure-Free Deployment

How Model Deployments Work

The platform handles all deployment steps automatically, from model packaging to API serving, with no manual configuration required.

Zero Manual Configuration

Deployment StatusACTIVEACTIVATEDEACTIVATE

Automated Model Deployment

Models deploy automatically after training completes. The platform handles infrastructure requirements, scaling, and model serving. Track deployment status and get notified when models are ready.

Internal & External Use

Multiple Access Methods

Use ML Clever dashboards, the prediction interface, or API integrations to consume deployed models—complete with documentation and keys.

Model Lifecycle

Version Control & Management

Manage multiple model versions, compare performance metrics, and control which versions are active. Roll back or deploy updates as data changes.

Access Options

How to Use Your Deployed Models

Access deployed models through dashboards for interactive use, the prediction interface for real-time predictions, or via API integration. Each deployment includes endpoint documentation and parameters.

See Deployment Options

Model Deployment Options

Trained Model
No Code Interface

Visual deployment for non-technical users

API Integration

Programmatic access for developers

  • Drag & Drop Interface
  • Pre-built Templates
  • REST Endpoints
  • Custom Integration

Technical Capabilities

Deployment Features

The deployment system handles infrastructure complexity while giving you multiple access options.

  • Automatic Deployment

    Post-Training

    Models deploy automatically when training completes.

  • Multi-Platform Access

    Flexible Use

    Access models via dashboards or API integration.

  • Performance Monitoring

    Real-Time

    Track model metrics and usage statistics.

Prediction Interface

Make predictions with deployed models through an intuitive interface. Enter input values or upload data files to receive instant results.

Prediction Interface

API Integration

External Application Access

Each deployed model generates a secure API endpoint with documentation. Integrate your models into external applications, dashboards, or systems using the provided API key and endpoint URL.

View API Documentation
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"
    }
}'

Security & Optimization

Deployment Management

Control who has access to your models while the platform handles scaling and resource optimization automatically.

  • Collaborative

    Cross-Team Access

    Models available to authorized team members.

  • Protected

    Secure Endpoints

    API access controlled via authentication keys.

  • Efficient

    Resource Optimization

    Compute resources scale based on usage.