Use Cases

Rassket excels in specific domains where domain-aware intelligence provides significant value. This page explores real-world use cases and how Rassket addresses them.

Energy Forecasting

Use Case: Energy Consumption Prediction

Problem: Predict hourly energy consumption for the next 24 hours to optimize grid operations and reduce costs.

Rassket Solution:

  • Select Energy → Forecasting domain
  • Upload historical consumption data with timestamps
  • Rassket automatically creates temporal features (hour-of-day, day-of-week, seasonality)
  • Generates lag features (consumption 1h ago, 24h ago, 7d ago)
  • Trains time-series-aware models
  • Provides energy-specific explanations

Outputs:

  • Forecast model with high accuracy
  • Feature importance showing peak hours and seasonal patterns
  • Domain-aware insights about consumption drivers
  • Export-ready model for integration into grid systems

Use Case: Renewable Energy Generation Forecasting

Problem: Predict solar/wind generation to balance supply and demand.

Rassket Solution:

  • Select Energy → Renewables domain
  • Upload weather data and historical generation
  • Rassket creates weather-dependent features
  • Models temporal patterns in renewable generation
  • Provides forecasts with uncertainty estimates

Research Time Series Analysis

Use Case: Experimental Data Analysis

Problem: Analyze experimental results to understand treatment effects and predict outcomes.

Rassket Solution:

  • Select Research → Experimental Analysis domain
  • Upload experimental data with treatment/control indicators
  • Rassket creates experimental design features
  • Applies appropriate statistical transformations
  • Provides research-contextualized explanations

Outputs:

  • Model with statistical significance testing
  • Feature importance showing treatment effects
  • Research-appropriate metrics and diagnostics
  • Export-ready model for further analysis

Use Case: Time Series Forecasting in Research

Problem: Forecast future values in a research time series dataset.

Rassket Solution:

  • Select Research → Forecasting domain
  • Upload time series data
  • Rassket applies research-appropriate transformations
  • Creates features respecting temporal structure
  • Provides forecasts with confidence intervals

Econometric Studies

Use Case: Economic Modeling

Problem: Model economic relationships and predict economic indicators.

Rassket Solution:

  • Select Research → Econometrics domain
  • Upload economic time series data
  • Rassket applies econometric-appropriate transformations
  • Creates interaction terms for economic relationships
  • Provides econometric-contextualized explanations

Outputs:

  • Model with interpretable coefficients
  • Feature importance showing economic drivers
  • Statistical diagnostics appropriate for econometrics
  • Export-ready model for economic analysis

Decision Intelligence Workflows

Use Case: Data-Driven Decision Making

Problem: Make strategic decisions based on data without deep ML expertise.

Rassket Solution:

  • Upload relevant data
  • Select appropriate domain
  • Rassket builds accurate models automatically
  • Provides domain-aware insights
  • Generates executive-ready reports

Outputs:

  • PDF executive reports for decision-makers
  • AI-powered insights explaining what matters
  • Forecasts and predictions for planning
  • Actionable recommendations

Use Case: Rapid Prototyping

Problem: Quickly prototype ML solutions to validate ideas before investing in full development.

Rassket Solution:

  • Upload sample data
  • Get working models in hours (not weeks)
  • Evaluate feasibility quickly
  • Export models for further development if promising
Rapid Iteration: Rassket enables rapid prototyping, allowing you to test multiple ideas quickly and focus development on the most promising approaches.

Grid Operations

Use Case: Demand Management

Problem: Predict peak demand to optimize grid operations and prevent outages.

Rassket Solution:

  • Select Energy → Grid domain
  • Upload historical demand data
  • Rassket identifies peak patterns
  • Creates features for demand forecasting
  • Provides grid-specific insights

Energy Economics

Use Case: Price Forecasting

Problem: Forecast energy prices for trading and procurement decisions.

Rassket Solution:

  • Select Energy → Energy Economics domain
  • Upload price and market data
  • Rassket models market dynamics
  • Creates features for price prediction
  • Provides market-contextualized insights

Statistical Modeling

Use Case: Advanced Statistical Analysis

Problem: Perform advanced statistical modeling on research data.

Rassket Solution:

  • Select Research → Statistical Modeling domain
  • Upload research dataset
  • Rassket applies statistical transformations
  • Creates appropriate interaction terms
  • Provides statistical-contextualized explanations

Common Patterns Across Use Cases

1. Domain Selection

All use cases benefit from selecting the appropriate domain, which enables:

  • Specialized feature engineering
  • Domain-appropriate model selection
  • Contextualized explanations

2. Automated Processing

Rassket handles:

  • Data preprocessing
  • Feature engineering
  • Model selection
  • Hyperparameter tuning
  • Evaluation

3. Actionable Outputs

All use cases receive:

  • Production-ready models
  • Comprehensive metrics
  • Domain-aware insights
  • Export-ready artifacts

Getting Started with Your Use Case

  1. Identify Your Domain: Choose Energy or Research based on your data
  2. Select Sub-Domain: Optionally refine to a specific sub-domain
  3. Prepare Your Data: Ensure CSV format with headers
  4. Upload and Train: Follow the dashboard workflow
  5. Export and Deploy: Use exported models in your systems
Not Sure? If your use case doesn't clearly fit Energy or Research, start with the base domain. Rassket will still build accurate models, and you can refine domain selection later.

Next Steps

Ready to apply Rassket to your use case?