PRD: HR Policy Inquiry Agent

Problem

HR and internal-support teams often spend a large share of handling time searching across policy documents before drafting an answer. The pain is not only search time. It is inconsistent interpretation, missing citations, slow escalation, and limited visibility into which documents create repeated demand.

Goal

Design an assistive AI Agent workflow that helps HR users locate relevant policy information, draft an answer with citations, and keep the final decision under human control.

The agent should reduce search and draft-preparation time while improving answer consistency and evidence traceability.

Non-goals

• The agent does not make final HR decisions.
• The agent does not send answers directly to employees without human review.
• The agent does not replace official policy owners.
• The agent does not use production-sensitive data in public demos.

Users

• HR operations user: searches policies and drafts answers.
• Policy owner: verifies policy interpretation and updates source documents.
• Employee requester: receives the final human-approved response.
• Governance reviewer: checks auditability, citations, and operating controls.

Core Workflow

1. HR user enters a question or selects an inquiry category.
2. Agent retrieves relevant policy passages from approved sources.
3. Agent produces a draft answer with citations and confidence notes.
4. Agent highlights ambiguity, missing evidence, or escalation triggers.
5. HR user reviews, edits, approves, or escalates.
6. The final answer and source evidence are logged.

Requirements

• Search approved policy sources.
• Return cited passages, not only free-form answers.
• Generate draft responses in a consistent format.
• Flag cases requiring human escalation.
• Record sources used, draft text, reviewer action, and final status.
• Version source documents and require citations or an explicit no-source-found state.

Success Metrics

• Search and draft-preparation time reduction.
• Citation coverage rate.
• Human correction rate.
• Escalation accuracy.
• User satisfaction from HR reviewers.
• Policy-document gap count discovered through repeated inquiries.

Risks and Guardrails

• Incorrect or outdated policy interpretation is handled through citation checks and human review.
• Over-trust is reduced by requiring reviewer approval before final responses.
• Prompt injection is mitigated by treating uploaded or copied text as untrusted input.
• Policy drift is controlled through approved repositories, source versioning, and audit logs.

Rollout Plan

• Phase 1: 10 representative inquiry types, offline evaluation, and HR reviewer feedback.
• Phase 2: small pilot with limited users and weekly quality review.
• Phase 3: wider rollout with SOP, training, support path, and policy-owner feedback loop.