Voice Commerce Engine for Real-Time In-Content Product Purchase
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Solution Overview
Problem
Current digital commerce solutions are fragmented and do not allow for seamless, real-time purchasing of products within audiovisual and immersive content environments, relying on static synchronization or manual user interactions, and lack integration with voice-driven commerce frameworks.
Innovation Solution
A voice-activated commerce engine that integrates product metadata, audiovisual stream analysis, and natural language processing to enable real-time product identification and purchase within the content environment, ensuring only verified products are presented, with secure transaction execution and a controlled monetization framework.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If static synchronization tables and predetermined web links are used for product identification, then the system can associate products with television programming, but the user must leave the viewing environment to complete a purchase and the commerce flow becomes fragmented
Solution Approach 1:
The patent merges product identification, information display, and purchase execution into a single integrated system that operates within the viewing environment. The commerce engine combines metadata processing, visual recognition, voice interaction, and transaction processing into one unified platform, eliminating the need for users to leave the viewing environment and creating a seamless commerce flow.
Solution Approach 2:
The commerce engine performs multiple functions through a single system: it processes metadata, analyzes visual content, recognizes products, displays information, and executes purchases. This multi-functional approach consolidates what were previously separate processes (product identification through one system, information display through another, purchase completion through a third) into a unified engine that handles the entire commerce journey.
2Measurement precision
If consumers manually upload images and wait for third-party seller responses, then product identification is possible, but the transaction process introduces delays and requires external vendor systems
Solution Approach 1:
The system performs preliminary actions by pre-processing and indexing product metadata, maintaining an updated product database, and pre-configuring transaction workflows. When a consumer asks about a product, the system already has the product information ready and can immediately provide accurate identification and purchase options without requiring manual image upload and third-party processing delays.
Solution Approach 2:
The commerce engine provides self-service by automatically processing product identification requests using its built-in visual recognition and metadata matching capabilities. Instead of requiring consumers to manually upload images and wait for external vendor processing, the system autonomously analyzes the product, retrieves information, and initiates transactions without external intervention or delays.
3Quantity of substance
If web-based platforms and mobile apps are used for product discovery, then product information can be accessed, but the solutions remain disconnected from audiovisual content and fail to leverage voice interaction
Solution Approach 1:
The patent merges web-based product databases, mobile application interfaces, audiovisual content streams, and voice interaction capabilities into a single integrated commerce engine. This unified system allows the engine to process metadata from web platforms, display product information through mobile app interfaces, analyze audiovisual content in real-time, and accept voice commands, thereby combining the strengths of previously separate systems into one versatile platform.
Solution Approach 2:
The commerce engine achieves universality by supporting multiple input methods (visual, auditory, textual) and multiple output channels (display, speech, haptic feedback) within a single system. It can process product information from web platforms, analyze audiovisual content, recognize voice commands, and execute transactions, making it adaptable to various contexts and integration requirements without requiring separate specialized systems.
4Ease of operation
If intelligent digital assistants are used for natural language interaction, then information retrieval and online shopping are possible, but they are not designed to integrate with live audiovisual streams or monetize content
Solution Approach 1:
The patent merges the natural language processing capabilities of intelligent digital assistants with live audiovisual stream analysis and content monetization functions into a unified commerce engine. The engine combines voice command processing, metadata analysis, visual recognition, and transaction execution into a single system that can naturally integrate with live content streams and enable real-time monetization, whereas traditional assistants handle information retrieval separately from content consumption and monetization.
Data Source
AI summary
The invention provides a system and method for enabling real-time, voice-activated commerce directly within audiovisual content. A viewer identifies and purchases products displayed in programming by issuing natural language commands. The system integrates merchant-uploaded “digital twins” of products, streaming content analysis via metadata or AI-powered visual recognition, and contextual interpretation of viewer queries. In some embodiments, the system supports multilanguage functionality, enabling automatic detection of a viewer's spoken language or selection of a preferred profile, with localized processing of queries and presentation of product information and overlays. The invention performs end-to-end commerce execution within the television or streaming platform, including product identification, presentation, and secure transaction using pre-linked payment accounts. A monetization framework ensures only registered and verified products are presented in response to queries, creating a controlled, scalable revenue model for brands and content originators. The system further extends into AR, VR, and mixed reality environments.