Client Seller Interfaces Using Structured Anonymous Engagement Data

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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 reflect user intent and personalize experiences.

Innovation Solution

A rules-based architecture that generates structured engagement data from anonymous users using declared intent, enabling privacy-respecting personalization and AI training without identity capture, and integrates deterministic logic to enhance human and AI agent interactions.

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 worsen

Engineering Contradiction:

Improvepersonalization capabilityVSAvoiddata accuracy

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent introduces an intermediary data structure (engagement data object with standardized fields) that mediates between raw user interactions and AI training requirements. This structured intermediary layer transforms unstructured behavior tracking data into reliable, schema-constrained engagement data, enabling accurate AI training while maintaining privacy through deterministic field mapping rather than probabilistic inference

Inventive Principle:

Principle #24Intermediary (Mediator)

2Manufacturing precision

If premature identity capture is used to generate structured data, then data structure is improved, but user privacy and trust worsen

Engineering Contradiction:

Improvedata structureVSAvoidprivacy intrusion

Core Design Contradiction:

Manufacturing precisionVSObject-affected harmful factors

Solution Approach 1:

The patent applies preliminary action by pre-defining the engagement data object schema with standardized fields before data collection occurs. This预先 established structure guides data capture during anonymous engagement phases, allowing structured data generation without requiring premature identity capture. The schema is prepared in advance but applied during anonymous interaction phases

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent inverts the conventional approach by starting with anonymous engagement data collection and only later associating it with user identities when provided. Instead of capturing identity first and then collecting data, the system collects structured engagement data anonymously first, then links to identity if the user chooses to provide it, reversing the traditional sequence to eliminate privacy intrusion

Inventive Principle:

Principle #13The other way round (Inversion)

3Quantity of substance

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

Engineering Contradiction:

Improvetraining data availabilityVSAvoidAI performance

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The patent implements feedback mechanisms where the AI system continuously learns from actual user interactions with the structured engagement data. The deterministic fields capture real-time user intent signals that provide immediate feedback to the AI model, allowing it to refine its understanding of user preferences and behaviors based on actual engagement patterns rather than relying solely on pre-aggregated inferred data

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250328842A1Systems And Methods For Creating And Operating A Client Seller User Interface For Engagement Platforms And Other Applications

Publication Date: 2025.10.23 PANKEY ERIC L

AI summary

Systems and methods are provided for creating and operating a client seller user interface relating to transactions (e.g., real estate or other transactions) and/or other information from engagement platforms and other applications. Robust system infrastructure integration, dynamic user interface creation, visualization of transaction progress, interactive responses mechanisms, and transaction status updates are provided to facilitate transactions and which can be used by human and/or artificial intelligence agents to enhance the particular application.