How to Prepare HRIS Data for AI Models and RAG with

Published in January 2026 and updated in October 2026, the guide explains how teams can use Unified.to’s HR & Directory API to retrieve normalized employee, compensation, payslip, timeshift, and time-off data from customer HRIS platforms for AI training and retrieval-augmented generation applications. Because HR systems represent compensation, payroll, employment status, leave, and termination differently, the API provides a common schema with standardized dates, enums, and linked IDs while preserving original currencies and payment frequencies for downstream processing. It outlines a Node.js workflow for configuring the SDK, paginating employee records, retrieving employee-specific payslips, optionally collecting timeshifts, normalizing employee fields, aggregating payroll history, and assembling training-ready records for JSONL files, feature stores, or model jobs. The guide emphasizes that integration coverage varies by provider, unsupported endpoints and missing data should be handled gracefully, and sensitive fields should be minimized and used only with appropriate customer approval. It also describes using normalized records and related policy content in RAG systems, with embeddings and vector indexes stored in the customer’s own infrastructure and updated through supported employee-change webhooks.

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