3 Key Questions to Ensure Your Property's AI is Built on the Right Data Foundation
Discover how property knowledge graphs empower AI to deliver accurate, personalized answers for multifamily.
8 Questions to Ask Before Investing in AI for Your Property
Choose AI wisely: Evaluate its data, compliance, automation, and personalization to create meaningful interactions.
5 Things Multifamily Professionals Should Consider When Choosing an AI Voicebot
Discover the 5 essential factors Multifamily agents need to consider when evaluating AI Voicebots for effective decision-making.
How Is An AI Mailbot The Perfect Companion for Multifamily Agents?
AI-powered mailbots automate email responses to save time, increase productivity, and allow the property team to focus on other critical responsibilities.
Is Your AI Chatbot Making Your Property Look Uninformed?
RAG helps multifamily AI provide accurate, reliable information on amenities, pricing, and neighborhood insight to ensure better resident and prospect experiences.
Why Are Private LLMs Hot Right Now?
The increasing attention to data security highlights the need for Private LLMs in multifamily to keep resident and prospect information safe and secure.
How NPU-Powered Technology Can Transform Multifamily Operations?
NPU-powered technology streamlines multifamily operations, automates routine tasks, and improves data security for more efficient management.
How Does A Multifamily Chatbot Understand Prospect Queries?
Vector databases turn information into special codes called embeddings. So, if you ask about the pets, the vector database can quickly find the right part of the pet policy. This makes searching fast and accurate.
How Can NLP Improve Multifamily Experiences?
NLP can translate our everyday language into computer language and then convert responses back from computer language into words we can easily understand.
Why Multifamily Chatbots Fail Without Embeddings?
Embeddings help chatbots recognize issues accurately. Without embeddings, multifamily chatbots might easily mix up inquiries due to their inability to understand the context.
