Intelligent Documentation Database Modernization

Role: UX & AI Research Lead | Client: Multi-Site Logistics Operations

Brief:
Transformed a fragmented, manual document management process into an AI-enabled centralized documentation database that provides real-time search, version control, and compliance tracking. Designed to support operational consistency across geographically distributed warehouses, the system integrates governance standards for data accuracy, role-based access, and regulatory compliance.

Key Objectives

• Consolidate scattered documents into a centralized, AI-searchable repository.

• Reduce time-to-locate critical documents for operational and compliance purposes.

• Implement AI-driven metadata tagging to improve discoverability and reduce human error in filing.

• Establish governance protocols for version history, audit logs, and access control.

Process & Responsibilities

• Conducted stakeholder interviews across multiple warehouse locations to identify critical documentation pain points.

• Collaborated with data engineering teams to integrate AI-enabled OCR (Optical Character Recognition) and natural language search capabilities.

• Designed role-based access structures to meet governance and compliance requirements (including ISO and industry safety standards).

• Led usability testing with warehouse staff to ensure the database UI supported rapid search and intuitive navigation.

• Implemented change management strategy to drive adoption across all operational sites.

Outcome

• Reduced average document retrieval time from 15 minutes to under 30 seconds.

• Achieved full traceability with automated version history and governance-compliant audit logs.

• Increased document search accuracy by 92% through AI-driven tagging and classification.

• Enhanced operational compliance with a centralized, verifiable repository.