Enterprise Gen AI Assistant

Background

  • Role: Business Analyst, Generative AI

  • Objective: To create a sophisticated, in-house AI-powered assistant using Azure Open AI APIs, tailored to meet the organization's specific needs and significantly enhance productivity across various functions.

  • Duration: 3 months

  • Key Responsibilities:

    • Scoping: Conducted extensive research to identify opportunities for AI integration within the organization's operations, with a focus on productivity enablement.

    • Roadmapping: Led the strategic planning process to outline the development roadmap for the Internal AI Assistant, emphasizing productivity enhancements.

    • Development Oversight: Collaborated with cross-functional teams to oversee the technical development, ensuring alignment with project objectives.

    • Use Case Identification: Worked closely with stakeholders to identify and prioritize use cases that would enable significant productivity gains.

    • Requirements Gathering: Gathered detailed requirements from end-users and subject matter experts to guide development.

    • Workforce Education: Developed training materials and conducted workshops to educate employees on how to leverage the AI assistant for productivity gains.

Overview

  • Issue Identification: Recognized the need to empower employees with an Internal AI Assistant that goes beyond content generation, focusing on productivity enablement.

  • Methodology: Implemented a comprehensive development strategy, leveraging Azure Open AI APIs to create a secure, user-friendly, and highly adaptable Internal AI Assistant with a strong emphasis on productivity features.

  • Challenges: Addressed technical complexities related to AI model integration, data privacy, and customized productivity workflows while ensuring a seamless user experience in a HIPAA-compliant environment.

  • Impact: Successfully launched the Internal AI Assistant, resulting in significant productivity gains across various functions, including data-intensive tasks, decision-making processes, and information retrieval.

  • Adoption Rate: Achieved over 50% daily usage across the enterprise, demonstrating the value and effectiveness of the AI assistant.

Skills and Tools

  • Skills: Product Management, Generative AI, Agile Development, Strategic Planning, User Experience Design, Stakeholder Engagement, Continuous Improvement.

  • Tools: Azure Open AI APIs, GPT-4, ChromaDB, SDLC, RAG, RLHF.

Features

  • Intuitive Interface

    Designed an intuitive interface that not only allows for easy model switching and conversation management but also integrates Retrieval-Augmented Generation (RAG). This RAG capability enables natural language access to company-specific data, significantly enhancing productivity and knowledge access.

  • Developer Enablement

    Established a Plugin Library, empowering developers to create customized solutions well in advance of the release of custom GPTs.

  • Workforce Education

    Actively engaged in educating the workforce on the use of the internal AI assistant, ensuring that employees are well-equipped to leverage its capabilities effectively.