Conversation Assistant Platform for Message Prioritization
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Solution Overview
Problem
In collaborative environments, users face information overload due to numerous notifications and messages across multiple messaging applications, leading to difficulties in prioritization and potential miscommunication, which can negatively impact business operations.
Innovation Solution
A conversation attendant and assistant platform that receives messages from various applications, tags them with a message cohort and amelioration actions, determines user context, and assigns a concern level, summarizing messages and delivering summaries through appropriate channels when the concern level exceeds a threshold, facilitating prioritization and action-taking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users engage with multiple messaging applications and collaborative tools, then communication coverage and information access improve, but information overload and difficulty in prioritization worsen
Solution Approach 1:
The system segments the overwhelming stream of messages into distinct cohorts based on conversation, sender, topic, or urgency. Each message cohort is then evaluated independently for risk and concern level, allowing users to process information in manageable chunks rather than facing a monolithic deluge of notifications.
Solution Approach 2:
The patent introduces an intermediary system (the messaging system with risk engine and prioritization engine) that sits between the user and multiple messaging applications. This intermediary automatically filters, prioritizes, and surfaces critical messages, relieving the user of the burden of manually managing information across numerous channels.
2Loss of information
If all messages and notifications are delivered to users, then information completeness improves, but user productivity and ability to take action worsen
Solution Approach 1:
The system performs preliminary actions by pre-evaluating messages for risk level and concern level before they reach the user. Critical messages are identified and surfaced in advance, allowing users to prioritize their attention and take action on important matters first, rather than wading through all messages chronologically.
Solution Approach 2:
The patent applies local quality by treating different messages differently based on their specific characteristics. Rather than uniform delivery, each message receives customized handling based on its cohort, risk level, and concern level, with critical messages receiving prominent placement and less critical messages being deferred or summarized.
3Reliability
If users manually monitor all conversations across multiple applications, then awareness of critical information improves, but time consumption and operational efficiency worsen
Solution Approach 1:
The system provides self-service by automatically monitoring, evaluating, and prioritizing messages without requiring user intervention. The risk engine and prioritization engine continuously analyze incoming messages, assign concern levels, and surface critical information, freeing users from the time-consuming task of manual monitoring while maintaining high awareness of critical matters.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors user interactions with surfaced messages and adjusts its prioritization accordingly. This feedback loop ensures that the system learns from user behavior patterns and improves its ability to predict and surface critical information, reducing the time users need to spend monitoring conversations.
Data Source
AI summary
A conversation attendant and assistant platform implements a method of receiving by a computer a plurality of messages in a plurality of conversations via one or more messaging applications. The platform tags each message of the plurality of messages with a message cohort and an amelioration action, and assigns a risk to the given message based on the message cohort. The platform also determines a user context of a user of the computer, and, in response to factors including the user context and the risk, assigns a concern level to the given message. The platform accumulates and summarizes the given message along with other messages in a conversation of the given message. In case the concern level exceeds a threshold, the platform selects one or more delivery channels for surfacing a summary of the conversation and surfaces the summary via the one or more delivery channels.