Customer-service staff were handling thousands of tenant calls each week and needed reliable answers quickly. Searching internal knowledge manually slowed calls and made consistency harder to maintain.

A RAG-based AI knowledge assistant uses semantic search, LLMs, source citations, call transcription, categorization, and workflow automation. Agents ask questions in natural language, receive answers grounded in approved knowledge-base articles, and can verify the source before responding to tenants.

• 3,000/weekCalls supported by faster knowledge access
• SecondsTime to retrieve answers
• Responses linked to source articles for verification
• Call transcription and categorization added for insight generation

Benchmarks are based on the original deployment; outcomes vary by process volume, complexity, and implementation scope. Similar workflow patterns can apply to businesses of different sizes.