MLOps automation in Rulex Platform
Managing machine learning (ML) operations can be complex, but Rulex Platform simplifies the process with an end-to-end MLOps solution.
From automating the tedious tasks of data preparation to continuously monitoring and tuning model performance, Rulex enables data teams to focus on what matters most: delivering business value.
MLOPS AUTOMATION
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How Rulex automates MLOps
Skip the boring tasks
Rulex eliminates the manual effort required in data ingestion, cleansing, and preparation by automating these steps.
With AutoML capabilities, Rulex helps you find the best features, tune hyperparameters, and compare algorithms to select the optimal model for each specific use case.
Monitor model performance
To maintain high-quality ML models, Rulex continuously monitors performance based on business-specific KPIs.
Early warnings detect signs of model drift, triggering alerts and initiating automated retraining processes to keep models accurate and reliable.
Retrain and fine tune the model
Human expertise can be incorporated into the process, creating feedback loops that blend ML-driven insights with expert knowledge.
This approach enables continuous model refinement, resulting in truly robust solutions.
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MLOps automation in action
IMPROVING DATA QUALITY WITH EXPERT FEEDBACK LOOPS
Rulex’s AI-driven data quality solution was embedded into the daily data operations of a F50 supply chain corporation, to boost the accuracy of foundational master data.
The solution not only autonomously identified the logical inconsistencies that frequently slip through standard business rule checks, but also integrated the domain knowledge of business experts in an expert feedback loop.
This resulted in continuous data quality through automated corrections and adaptive processes, aligning with the key MLOps principle of continuous improvement.
ACCELERATING TASKS AND PROCESS INTEGRATION
Rulex implemented an AutoML-driven demand forecasting solution for a global pharmaceutical company, integrating data pre-processing, modeling, and forecasting.
Rulex Platform incorporated sales data and external variables like geographic information, automatically selecting the best-fit model and enabling parallel testing and execution.
Forecasts over a three-month horizon included automated re-runs with new data to maintain high accuracy. This all-in-one solution seamlessly integrated forecasts into inventory and logistics processes.
ASSESSING CREDITWORTHINESS
Rulex provided a major Italian bank with a solution to assess the credit reliability of private, small business, and corporate subjects using various models (e.g., transactional, sociodemographic, behavioral).
Once weighted scores were unified, the result was fine-tuned via the integration of expert-driven rules. Real-time alerts flagged model performance decay, triggering model re-extraction and reconfiguration, with reports documenting drops and the new optimal settings.
The solution analyzed 1 million credit positions daily and could be integrated at any stage of the scoring pipeline.
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