Rules-Based Message Records for Anonymous Real Estate Engagement

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Solution Overview

Problem

Current engagement platforms rely heavily on behavior tracking or premature identity capture, leading to a lack of actionable data, privacy risks, and inaccurate AI training, failing to provide personalized and seamless experiences in real estate transactions.

Innovation Solution

A rules-based architecture that captures structured engagement data from anonymous users using declared intent, enabling privacy-respecting personalization and AI training, and facilitating seamless transitions without identity capture.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If behavior tracking is used to personalize user experiences, then personalization capability is improved, but privacy risks and data accuracy deteriorate

Engineering Contradiction:

Improvepersonalization capabilityVSAvoiddata accuracy

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent introduces an intermediary mechanism using deterministic logic rules that act as a mediator between user behavior data and AI training. Instead of directly training AI on raw behavioral data (which causes accuracy and privacy issues), the system transforms behaviors into structured engagement data through rule-based processing, creating a buffer layer that improves both privacy compliance and data quality for AI training

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system changes the parameter representation from raw behavioral data to structured engagement data with specific fields (engagement_id, user_id, content_id, engagement_type, timestamp). This parameter transformation enables the data to maintain personalization capability while improving accuracy and privacy compliance through standardized, cleaned data structures

Inventive Principle:

Principle #35Parameter changes

2Quantity of substance

If behavior tracking is used to generate user data, then data volume is increased, but data quality and privacy compliance deteriorate

Engineering Contradiction:

Improvedata volumeVSAvoiddata quality

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The patent extracts only the essential, high-quality engagement information from the vast amount of raw behavioral data. By filtering and selecting only relevant engagement events (views, clicks, interactions) and transforming them into structured records, the system reduces data volume to a manageable, high-quality subset that maintains measurement precision and privacy compliance

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system implements feedback mechanisms where engagement data is continuously validated and refined through rule-based processing. The deterministic logic rules provide feedback loops that ensure data quality standards are met before the data is used for AI training, creating a quality-assured data pipeline

Inventive Principle:

Principle #23Feedback

3Quantity of substance

If AI systems are trained on inferred data, then training data availability is improved, but AI performance and relevance deteriorate

Engineering Contradiction:

Improvetraining data availabilityVSAvoidAI performance

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The system performs preliminary action by structuring and validating engagement data before it is used for AI training. The rule-based processing occurs in advance to transform raw behaviors into clean, structured engagement records, ensuring the data is ready for AI training without requiring additional processing or inference steps that would reduce performance

Inventive Principle:

Principle #10Preliminary action

4Adaptability or versatility

If user identity is captured early to enable personalization, then personalization capability is improved, but user privacy and trust deteriorate

Engineering Contradiction:

Improvepersonalization capabilityVSAvoiduser privacy risk

Core Design Contradiction:

Adaptability or versatilityVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary personalization actions using anonymous engagement data before user identity is captured. By structuring and processing engagement behaviors into structured engagement data in advance, the system enables personalization capabilities without requiring immediate identity disclosure, thereby reducing privacy risks while maintaining personalization effectiveness

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250328971A1Systems And Methods For Building A Message Record And Managing Communications Relating To Real Estate Transactions

Publication Date: 2025.10.23 PANKEY ERIC L

AI summary

Systems and methods are provided for building message records and managing communications relating to transactions (e.g., real estate or other transactions) and/or other information from engagement platforms and other applications. System architecture and integration, customizable message creation, dynamic message retrieval, client type and information, and market trends and client specialty values are used to provide efficient communication management, personalized client engagement, real-time updates and responsiveness, comprehensive information delivery, and adaptability to client specifics to facilitate transactions and which can be used by human and/or artificial intelligence agents to enhance the particular application.