AI for Global People Ops

Automating Global HR Workflows with Accuracy, Speed, and Local Expertise.

DRL Team

AI R&D Center

6 min read

Content

Summary Tech Challenge Solution Impact

Summary

Managing a global workforce presents significant challenges for HR teams. Navigating complex employment laws, ensuring compliance across multiple jurisdictions, and handling administrative tasks are resource-intensive processes that consume valuable time.
To solve this, we built a domain-specific AI agent for global HR operations, powered by a custom retrieval-augmented generation (RAG) system. This assistant delivers real-time, policy-grounded responses to compliance queries across 20+ countries, automates contract generation and expense tracking workflows, and supports multilingual interactions.
This system transforms how HR teams scale globally: reducing legal risk, accelerating operations, and enabling lean teams to operate across borders with confidence.

Tech Stack

Python

OpenAI

Anthropic

Milvus

Cohere

Retrieval-Augmented Generation (RAG)

Milvus Vector Database

AWS

Tech Challenge

Global Compliance Complexity. Labor laws vary significantly across jurisdictions. The system needed to maintain an accurate understanding of regulatory nuance across over supported countries.
Precision in Retrieval and Reasoning. It was critical that the agent retrieve the right legal policies or internal rules and present grounded answers without hallucinations.
Cross-Language Capabilities. Supporting native-language HR teams meant the system had to natively understand and respond in multiple languages.
Latency in RAG Workflows. The assistant needed to behave interactively. Real-time retrieval and answer generation with clear citations had to happen in under a few seconds.
Security and Privacy. Working with sensitive employee information, the system had to enforce strict data access and encryption.

Solution

RAG Stack with Milvus indexes HR policy manuals, international labor law documents, and region-specific templates. Every response is grounded in real-time, context-specific documents.
We employ multilingual embeddings and structured prompting to natively support user queries in different languages, enabling globally distributed teams to interact in their preferred language.
Conversational Core with OpenAI models powers the assistant’s reasoning engine, with domain-specific prompting layers to enforce legal and HR relevance.
We integrated the action layer with Function Calling. The agent connects with internal systems (HRIS, document stores, legal templates) and can execute tasks such as generating compliant employment agreements or pulling historical leave data.
The system masks PII before LLM interaction, maintains auditable logs, and has strict role-based access control.

Impact

Tasks such as employment contract drafting or international compliance lookups are now completed up to 45% faster.
In internal evaluations, responses from our system were preferred by HR and legal professionals over those from general-purpose LLMs, due to clearer sourcing and policy adherence.
Multilingual streaming interfaces and accurate, context-aware answers have significantly increased daily active usage across HR teams.
Companies are set to cut down on external legal consultations and reduce overhead by automating routine, error-prone processes such as compliance checks, leave audits, and policy dissemination.

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