LLM Interface for Intent-Based Systems-of-Record Connections
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Solution Overview
Problem
Property management companies face challenges in providing timely and personalized responses to residents due to the complexity of document corpuses and multiple systems of record, leading to poor response times and unmet needs, especially during high request volumes.
Innovation Solution
An interface utilizing a Large Language Model (LLM) processes resident requests through an omnichannel system, determining intent and generating responses using a knowledge base or escalating to human managers as needed, while integrating with systems of record for data retrieval and updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If property management companies manually process resident requests through multiple systems of record, then they can provide personalized responses, but response times deteriorate and workload increases during high request volumes
Solution Approach 1:
An AI assistant is introduced as an intermediary between residents and property management systems. The assistant automatically connects to multiple systems of record, retrieves relevant information, and generates personalized responses without requiring direct human intervention for each request, thus maintaining response quality while reducing response time
Solution Approach 2:
The system enables self-service automation where the AI assistant independently queries multiple systems of record, synthesizes information, and generates responses autonomously. This allows the system to serve itself in processing routine resident requests, freeing property managers from manual workload while maintaining personalized service quality
2Loss of information
If property management companies integrate with multiple systems of record, then they can access comprehensive resident data, but system complexity increases
Solution Approach 1:
The AI assistant is designed with multi-functional capabilities to interact with various types of systems of record including property management software, document management systems, and communication platforms. A single unified interface handles diverse data sources, reducing the need for separate integration mechanisms for each system and simplifying overall system complexity
Solution Approach 2:
The AI assistant serves as a mediating layer that abstracts the complexity of multiple system integrations. Instead of creating direct connections between numerous systems, the assistant centralizes data access through a single interface, managing all connections to systems of record from one point and thereby reducing integration complexity
3Reliability
If property managers handle all resident inquiries manually, then they can ensure accurate personalized service, but productivity decreases during high request volumes
Solution Approach 1:
The AI assistant performs self-service by autonomously accessing multiple systems of record, retrieving relevant resident information, and generating accurate personalized responses without human intervention. This automated self-service capability maintains service accuracy while dramatically increasing productivity during high request volumes
Solution Approach 2:
The system incorporates feedback mechanisms where the AI assistant continuously learns from interactions and system responses. By analyzing successful response patterns and system feedback, the assistant improves its accuracy over time while maintaining high throughput, ensuring both reliability and productivity
Data Source
AI summary
Provided are computer-implemented systems and methods for connecting to plurality of systems of record. This includes receiving a user request from the user at a user device, transmitting the user request via a network, receiving a first output based on the user request, determining one or more actions, based on the one or more intent signals, each of the one or more intent signals identifying a user intent in the user request, determining a candidate system of record associated with the one or more actions, transmitting an automated request based on the one or more intent signals and the one or more actions, receiving a second output based at least on the one or more intent signals and the one or more actions, the second output comprising a response to the user request, determining a user response to the user request based on the second output.