Merge Docs

Train AI with HRIS data

HRIS

Efficiently train data models using employee data and compensation data

1. Authentication and connection

Your users authorize your application to access their HRIS platform by going through an authorization flow using Merge Link.

2. Data retrieval from HRIS

Utilize Merge's API endpoints, such as GET /employees and GET /EmployeePayrollRun, to retrieve comprehensive HRIS data related to employees and compensation.

3. Data pre-processing

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. Model evaluation

Validate the model's performance using the testing set. Compute relevant metrics to gauge the model's effectiveness.

6. Feedback loop

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 HR insights

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.