Train AI with HRIS data
1. User authorizes HRIS access
Your users authorize your application to access their HRIS platform by going through an authorization flow using Merge Link.
2. Retrieve comprehensive HRIS data
Utilize Merge’s API endpoints, such as GET /employees and GET /EmployeePayrollRun, to retrieve comprehensive HRIS data related to employees and compensation.
3. Clean and transform data
Clean the data by removing duplicates in your customer data, handling missing values, and filtering out irrelevant fields. Transform data into a format suitable for AI training, possibly involving normalization, encoding, or feature engineering.
4. Model training
Split the preprocessed HRIS data into training and testing sets. Use the training set to train an AI model tailored for workforce analytics and optimization tasks and insights.
5. Validate model performance
Validate the model’s performance using the testing set. Compute relevant metrics to gauge the model’s effectiveness.
6. Monitor and retrain
Continuously monitor HRIS data for updates, changes, and new employee information and implement a feedback loop for model retraining and improvement to adapt.
7. Surface insights to customers
Build a UI to provide your customers with valuable insights generated by the AI models, such as employee retention predictions, compensation optimization recommendations, or performance trend analysis.
