公开(公告)号：US12032918B1

公开(公告)日：2024-07-09

申请号：US18240627

申请日：2023-08-31

申请人： Wevo, Inc.

发明人： Dustin Garvey ,  Charlie Hoang ,  Alexa Stewart ,  Janet Muto ,  Nitzan Shaer ,  Andrea Paola Aguilera García ,  Jon Andrews ,  Frank Chiang

IPC分类号： G06F40/40

CPC分类号： G06F40/40

摘要： Techniques are described herein for using artificial intelligence to select, curate, normalize, enrich, and synthesize the results of user experience (UX) tests. In some embodiments, a system identifies a set of unstructured textual elements associated with one or more UX tests. The system may configure agents using generative language model services, including a reviewing agent that reviews and edit outputs of a machine learning classification model applied to the unstructured textual elements and/or a curating agent that selects unstructured textual elements to represent themes within the user experience test classified using the machine learning classification model. The outputs may be used to enhance the scalability, function, and efficiency of applications directed at improving product designs.

公开(公告)号：US20240144356A1

公开(公告)日：2024-05-02

申请号：US17981252

申请日：2022-11-04

申请人： WEVO, INC.

发明人： Dustin Garvey ,  Shannon Walsh ,  Frank Chiang ,  Janet Muto ,  Nitzan Shaer ,  Charlie Hoang ,  Hannah Sieber ,  Nick Montaquila ,  Jessica Yau ,  Joseph Gibson ,  Mary McMurray ,  Laurie Delaney ,  Andrea Paola Aguilera García ,  Alexa Stewart

IPC分类号： G06Q30/06 ,  G06Q30/02

CPC分类号： G06Q30/0641 ,  G06Q30/0201 ,  G06Q30/0203

摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system receives input defining or modifying a theme schema for classifying results of user experience tests. Responsive to receiving the input, the system trains a themer model based at least in part on example classifications in a training dataset, where the classifications map results to themes within the theme schema. When a new set of results for a user experience test is received, the trained machine learning model may generate a set of predicted themes to classify the test results. The output of the model may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.

公开(公告)号：US11972442B1

公开(公告)日：2024-04-30

申请号：US18111444

申请日：2023-02-17

申请人： Wevo, Inc.

发明人： Dustin Garvey ,  Shannon Walsh ,  Frank Chiang ,  Janet Muto ,  Nitzan Shaer ,  Hannah Sieber ,  Charlie Hoang ,  Alexa Stewart ,  Keith Horvath ,  Marshall McCready ,  Laurie Delaney ,  Jon Andrews

IPC分类号： G06Q30/018 ,  G06F9/451

CPC分类号： G06Q30/0185 ,  G06F9/451

摘要： Techniques and embodiments are described herein for detecting and mitigating fraudulent activity within user experience (UX) test applications. In some embodiments, a system applies a set of rules and/or machine learning (ML) models to each respondent of an online survey or UX test. Different ML models may be trained to learn domain-specific patterns indicative of fraudulent activity. The system may then select the ML models based on attributes of the UX test and/or respondent. The selected rules and/or ML models may generate a probabilistic score representing a likelihood that the respondent is currently engaging in or will engage in fraudulent activity with respect to a UX test. If the score exceeds a threshold, then the system may take action to mitigate the fraudulent activity, such as triggering the removal of the user from an accepted respondent pool, halting further engagement between the respondent and the UX test, and generating alerts.

公开(公告)号：US20240354792A1

公开(公告)日：2024-10-24

申请号：US18457178

申请日：2023-08-28

申请人： Wevo, Inc.

发明人： Frank Chiang ,  Dustin Garvey ,  Alexander Barza ,  Alexa Stewart ,  Charlie Hoang ,  Jon Andrews ,  Hannah Sieber ,  Jessica Yau ,  Shachar Koresh ,  Janet Muto ,  Nitzan Shaer

IPC分类号： G06Q30/0204 ,  G06Q10/0631

CPC分类号： G06Q30/0204 ,  G06Q10/063112

摘要： Operations of a prompt management system are disclosed. The operations may include: receiving a prompt for performing a set of tasks, assigning an agent group that includes a plurality of agents to perform a set of roles associated with a dataset in support of the set of tasks, causing the plurality of agents to perform the set of roles using a first machine-learning model, receiving a set of role results from the plurality of agents responsive to performing the set of roles, performing the set of tasks using at least a second machine-learning model, and providing a task result for display on a user interface device. The set of tasks may include executing an operation on the set of role results using the second machine-learning model, and generating a task result that includes a product of the operation executed on the set of role results.

公开(公告)号：US20240320591A1

公开(公告)日：2024-09-26

申请号：US18505951

申请日：2023-11-09

申请人： Wevo, Inc.

发明人： Dustin Garvey ,  Frank Chiang ,  Alexa Stewart ,  Janet Muto ,  Andrea Paola Aguilera García ,  Nitzan Shaer ,  Alexander Barza

IPC分类号： G06Q10/0637 ,  G06F11/34 ,  G06F16/34 ,  G06F30/27 ,  G06Q30/0203

CPC分类号： G06Q10/0637 ,  G06F11/3438 ,  G06F16/345 ,  G06F30/27 ,  G06Q30/0203

摘要： Techniques are described herein for using artificial intelligence (AI) and machine learning (ML) to automate, accelerate, and enhance various aspects of comparative user experience testing. Embodiments interface with generative language models to compare user experiences and summarize the results of the comparison. In some embodiments, automated systems and programmatic processes access a series of analysis contexts, where a context includes a collection of message content fragments. The systems and processes may use the message content fragments for a given context to construct a dialogue with a generative language model to compare separate user experiences based on the results of a set of user experience tests. The output of the generative language model at one stage of the analysis may be combined with content fragments for another context to craft a dialogue at another stage of the analysis and/or to perform additional analyses of the user experiences.

公开(公告)号：US20240319965A1

公开(公告)日：2024-09-26

申请号：US18505935

申请日：2023-11-09

申请人： Wevo, Inc.

发明人： Dustin Garvey ,  Nitzan Shaer ,  Janet Muto ,  Alexa Stewart ,  Frank Chiang ,  Hannah Sieber ,  Charlie Hoang ,  Alexander Barza

IPC分类号： G06F8/20 ,  G06F40/40

CPC分类号： G06F8/20 ,  G06F40/40

摘要： Techniques are described herein for using artificial intelligence (AI) and machine learning (ML) to automate, accelerate, and enhance various aspects of user experience testing. Embodiments incorporate generative language models into user experience testing applications to extract key findings for improving product designs and driving product optimizations. In some embodiments, programmatic processes conduct a dialogue with a generative language model by engineering a set of input prompts as a function of prompt fragments, user experience test results, and test contexts. The AI-generated findings may drive actions directed to optimizing product designs and improving user experiences.

公开(公告)号：US12106318B1

公开(公告)日：2024-10-01

申请号：US18457178

申请日：2023-08-28

申请人： Wevo, Inc.

发明人： Frank Chiang ,  Dustin Garvey ,  Alexander Barza ,  Alexa Stewart ,  Charlie Hoang ,  Jon Andrews ,  Hannah Sieber ,  Jessica Yau ,  Shachar Koresh ,  Janet Muto ,  Nitzan Shaer

IPC分类号： G06Q30/0204 ,  G06Q10/0631

CPC分类号： G06Q30/0204 ,  G06Q10/063112

摘要： Operations of a prompt management system are disclosed. The operations may include: receiving a prompt for performing a set of tasks, assigning an agent group that includes a plurality of agents to perform a set of roles associated with a dataset in support of the set of tasks, causing the plurality of agents to perform the set of roles using a first machine-learning model, receiving a set of role results from the plurality of agents responsive to performing the set of roles, performing the set of tasks using at least a second machine-learning model, and providing a task result for display on a user interface device. The set of tasks may include executing an operation on the set of role results using the second machine-learning model, and generating a task result that includes a product of the operation executed on the set of role results.

公开(公告)号：US20240281837A1

公开(公告)日：2024-08-22

申请号：US18111441

申请日：2023-02-17

申请人： Wevo, Inc.

发明人： Jon Andrews ,  Charlie Hoang ,  Dustin Garvey ,  Frank Chiang ,  Hannah Sieber ,  Keith Horvath ,  Mary McMurray ,  Nitzan Shaer ,  Shannon Walsh

IPC分类号： G06Q30/0203

CPC分类号： G06Q30/0203

摘要： Techniques and embodiments described herein include a scalable system for integrating panel-based research with user experience (UX) testing tools, such as online survey applications. The techniques provide for the parallelization of a single request across multiple panel providers. The parallelization across multiple panel providers may occur transparently to users, including the designers of UX testing tools and methodologies, without requiring any complex modifications of the underlying source code. The parallelization may further significantly reduce request processing speeds within the system. Additionally or alternatively, the techniques provide for runtime adjustments of configurations to adjust rates at which respondents with varying attributes are fielded. As a result, qualified UX test respondents may be fielded much more quickly, increasing system scalability by allowing the system to process more requests within a given timeframe.

公开(公告)号：US20240144297A1

公开(公告)日：2024-05-02

申请号：US17979231

申请日：2022-11-02

申请人： WEVO, INC.

发明人： Dustin Garvey ,  Shannon Walsh ,  Frank Chiang ,  Janet Muto ,  Nitzan Shaer ,  Charlie Hoang ,  Hannah Sieber ,  Nick Montaquila ,  Jessica Yau ,  Joseph Gibson ,  Mary McMurray ,  Laurie Delaney ,  Andrea Paola Aguilera García, I ,  Alexa Stewart

IPC分类号： G06Q30/02

CPC分类号： G06Q30/0201 ,  G06Q30/0203

摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system receives input defining or modifying a theme schema for classifying results of user experience tests. Responsive to receiving the input, the system trains a themer model based at least in part on example classifications in a training dataset, where the classifications map results to themes within the theme schema. When a new set of results for a user experience test is received, the trained machine learning model may generate a set of predicted themes to classify the test results. The output of the model may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.

公开(公告)号：US11836591B1

公开(公告)日：2023-12-05

申请号：US17981243

申请日：2022-11-04

申请人： WEVO, INC.

发明人： Dustin Garvey ,  Shannon Walsh ,  Nitzan Shaer ,  Janet Muto ,  Jon Andrews ,  Frank Chiang ,  Alexa Stewart ,  Hannah Sieber ,  Charlie Hoang ,  Rick Alarcon Sisniegas ,  Alexander Barza

IPC分类号： G06N20/20

CPC分类号： G06N20/20

摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience tests. In some embodiments, a system identifies a qualitative element within a result set for a user experience test. The system then selects a machine learning model to apply based on one or more attributes associated with the user experience test and generates a predicted visibility, quality, and/or relevance for the qualitative element. Based on the prediction, the system generates a user interface that curates a set of results of the user experience test.