Overlay Content Capture for Privacy-Preserving Context Assistance
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Solution Overview
Problem
Conventional web-based customer service chat interfaces require manual user input to describe issues, leading to inefficiency, frustration, privacy concerns, and lack of context awareness, and they lack continuity across devices and enterprise policy enforcement.
Innovation Solution
An overlay-based capture system that automatically captures underlying content using semi-transparent overlays, DOM snapshots, and pixel-buffer grabs, applies privacy filters, and synchronizes responses across devices, with enterprise policy enforcement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual user input is required to describe issues in conventional chat interfaces, then user control over the conversation is maintained, but efficiency decreases and user frustration increases
Solution Approach 1:
The system enables self-service by automatically capturing the underlying content through the overlay interface without requiring manual user input. The capture module autonomously identifies and extracts relevant content from the host application, eliminating the need for users to manually describe issues while maintaining user control over the conversation flow.
Solution Approach 2:
The patent replaces the mechanical action of manual typing and description with an automated optical capture mechanism. The overlay interface captures visual content from the host application and converts it into structured data for the chat bot, substituting manual input operations with automated content extraction and analysis.
2Loss of information
If screenshots or remote access are used to share context, then the system gains awareness of the issue, but privacy and security concerns arise
Solution Approach 1:
The system extracts only the necessary content information through the overlay interface without capturing sensitive system-level data. The capture module selectively extracts relevant visual and textual content from the host application while excluding sensitive information, thereby achieving context awareness without compromising privacy or security.
Solution Approach 2:
The overlay interface acts as an intermediary layer between the user's host application and the chat bot system. This intermediary captures and transmits only the necessary contextual information while filtering out sensitive data, serving as a secure bridge that enables context sharing without direct system access or privacy violations.
3Extent of automation
If the overlay interface captures underlying content automatically, then context awareness is improved and manual input is eliminated, but device complexity increases
Solution Approach 1:
The overlay interface is designed as a universal component that can capture various types of content from different host applications through a single unified mechanism. The same overlay infrastructure handles multiple content types (images, text, layouts) and multiple applications, reducing overall system complexity through multi-functionality rather than requiring separate capture mechanisms for each use case.
4Reliability
If the system analyzes captured content to provide contextual responses, then assistance quality improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary content extraction and pre-processing within the overlay interface before transmitting data to the chat bot for analysis. By preparing and structuring the captured content in advance, the system reduces the computational burden during analysis and accelerates the overall response time while maintaining high accuracy through structured data preparation.
Data Source
AI summary
Systems and methods are provided for delivering context-aware assistance through an overlay interface. An overlay rendered on a user device captures content of a host application underlying the overlay via a scan-snap process. Captured content is filtered by privacy controls, transmitted securely to a server, analyzed to determine contextual meaning, and used to generate a response displayed in the overlay. In certain embodiments, capture includes document object model (DOM) snapshots, pixel-buffer screenshots, or fusion of DOM and bitmap data, optionally preceded by lightweight on-device optical character recognition. Mobile embodiments invoke the overlay through gesture inputs, while desktop embodiments employ a clipping interface with live preview of the selected capture region. Enterprise-oriented embodiments enforce policy restrictions, mask sensitive fields, and maintain audit logs, while multi-device embodiments synchronize responses across mobile and desktop sessions. The system thereby enables accurate, privacy-preserving contextual assistance without requiring remote access or manual user explanation.