Content-First Interaction Platform for Conversational App Development
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Solution Overview
Problem
Current conversational interaction application development requires manual creation of interaction models, endpoint business logic, and content, which is time-consuming and inflexible, especially when handling multiple intents and platforms, and often necessitates redeployment for changes.
Innovation Solution
A content-first development platform with a pre-populated general interaction model that uses graph traversal and content index searching, allowing for abstract intents and open-ended slots, enabling developers to create content without coding and deploy across multiple assistant platforms without specific configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual creation of interaction models and endpoint business logic is used, then customization and precision are improved, but development time and complexity increase
Solution Approach 1:
The patent applies preliminary action by providing pre-configured interaction models, templates, and content libraries that are prepared in advance. Developers can directly utilize these pre-built components without creating them from scratch, significantly reducing development time while maintaining the ability to customize specific elements as needed.
Solution Approach 2:
The patent implements copying by allowing developers to reuse existing interaction models, content templates, and business logic patterns across multiple projects and platforms. This copying mechanism enables rapid deployment while maintaining consistency and precision through proven templates that can be adapted to specific needs.
2Adaptability or versatility
If platform-specific configuration is required for each assistant platform, then platform compatibility is improved, but deployment complexity and time increase
Solution Approach 1:
The patent applies universality by creating a platform-agnostic interaction model that can be deployed across multiple assistant platforms (Amazon Alexa, Google Assistant, Microsoft Cortana) without requiring separate configurations. The system uses a universal content framework that automatically adapts to different platforms, reducing deployment complexity while maintaining broad platform compatibility.
3Measurement precision
If exact matching of utterances to sample utterances is required, then intent accuracy is improved, but flexibility and adaptability decrease
Solution Approach 1:
The patent implements feedback by incorporating machine learning models that learn from actual user interactions and utterance patterns. The system continuously improves its intent recognition by analyzing real-world usage data, allowing it to maintain high accuracy while becoming increasingly flexible in handling varied user expressions and natural language variations.
Data Source
AI summary
Among other things, a developer of an interaction application for an enterprise can create items of content to be provided to an assistant platform for use in responses to requests of end-users. The developer can deploy the interaction application using defined items of content and an available general interaction model including intents and sample utterances having slots. The developer can deploy the interaction application without requiring the developer to formulate any of the intents, sample utterances, or slots of the general interaction model.