Overview
Designed and deployed an AI-powered chatbot using SharePoint + OpenAI RAG to retrieve LADWP technical standards, achieving ~80% faster lookup speed and higher accuracy than existing tools. Also developed a revenue recovery system to detect unmetered Accessory Dwelling Units (ADUs) from 80K+ work requests, flagging 206 high-risk cases.
Impact
Compared to manual search through technical documents
Projected usage across Power division
With multi-million dollar scaling potential
From 80,000+ work requests analyzed
Tech Stack
Key Features
AI-Powered Technical Standards Retrieval
Built RAG (Retrieval-Augmented Generation) system to help LADWP engineers quickly find technical standards and documentation, replacing slow manual search processes.
Revenue Recovery System
Developed automated detection system for unmetered Accessory Dwelling Units (ADUs), analyzing work request data to identify properties that should be billed for electricity but aren't currently.
OCR Integration
Implemented Tesseract OCR to extract text from scanned technical documents, enabling comprehensive search across both digital and legacy paper-based standards.
SharePoint Integration
Seamlessly integrated with existing LADWP infrastructure through SharePoint and Microsoft 365, ensuring easy adoption without disrupting current workflows.
Challenges & Solutions
Challenge: Legacy Document Formats
Solution: Implemented multi-format data extraction pipeline using Tesseract OCR for scanned documents and custom parsers for various digital formats, ensuring comprehensive coverage of LADWP's technical library.
Challenge: Massive Work Request Dataset
Solution: Developed efficient data processing pipeline to analyze 80,000+ work requests, using pattern matching and machine learning techniques to identify high-risk ADU cases with high precision.
Challenge: Enterprise Security & Compliance
Solution: Worked within LADWP's security requirements by leveraging Microsoft's existing infrastructure (SharePoint, Copilot Studio) and ensuring all data remained within the organization's secure environment.
Feedback
"This tool could scale department-wide, even to Water [division]."
— LADWP Staff Feedback