Patents by Inventor Ved Surtani
Ved Surtani has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240161068Abstract: A device receives current vehicle data that describes a current state of each of a plurality of components of the vehicle. The device accesses historical data describing prior services previously performed on the vehicle and applies the current vehicle data and the historical vehicle data to a trained machine learning model to obtain a set of recommended services, where the model was trained using labeled training data associated with additional vehicles having a threshold similarity to the vehicle. The machine learning model is trained to output a set of recommended services to be performed for a given vehicle based on inputs of given current vehicle data and given historical vehicle data for the given vehicle. The device outputs for display the set of recommended services to be performed on the vehicle to a user.Type: ApplicationFiled: January 24, 2024Publication date: May 16, 2024Inventors: Nitika Gupta, Ved Surtani, Justin Alexander Chi-Young Hou
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Patent number: 11956278Abstract: A document management system manages documents of an entity. The document management system monitors for entries in a document that are suspicious. Entries in the document are classified by the document management system as a “suspicious entry” or a “non-suspicious entry.” In one embodiment, a suspicious entry is indicative of potentially suspicious activity at the entity.Type: GrantFiled: January 24, 2023Date of Patent: April 9, 2024Assignee: Tekion CorpInventors: Satyavrat Mudgil, Anant Sitaram, Ved Surtani
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Patent number: 11934967Abstract: A management system operates in conjunction with entities to provide component recommendations for objects. The management system trains a machine learning model used to generate the component recommendations. The machine learning model is trained based on historical component entries describing components previously provided and identifiers of the components. The management system generates training data by classifying the historical component entries into predetermined component classifications. After the machine learning model is trained, the management system generates a customized recommendation of components for an object based on likelihoods of selection of the predetermined component classifications.Type: GrantFiled: March 22, 2023Date of Patent: March 19, 2024Assignee: Tekion CorpInventors: Jayaprakash Vijayan, Ved Surtani, Nitika Gupta, Pratheek Manjunath Bharadwaj, Indrajit Saha
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Patent number: 11922378Abstract: A device receives current vehicle data that describes a current state of each of a plurality of components of the vehicle. The device accesses historical data describing prior services previously performed on the vehicle and applies the current vehicle data and the historical vehicle data to a trained machine learning model to obtain a set of recommended services, where the model was trained using labeled training data associated with additional vehicles having a threshold similarity to the vehicle. The machine learning model is trained to output a set of recommended services to be performed for a given vehicle based on inputs of given current vehicle data and given historical vehicle data for the given vehicle. The device outputs for display the set of recommended services to be performed on the vehicle to a user.Type: GrantFiled: December 10, 2021Date of Patent: March 5, 2024Assignee: Tekion CorpInventors: Nitika Gupta, Ved Surtani, Justin Alexander Chi-Young Hou
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Patent number: 11886511Abstract: Systems and methods are disclosed herein for machine-learned vehicle desking operations. A vehicle recommendation system receives a request to determine similarities between vehicles. The request can indicate an identifier of a user-specified vehicle associated with vehicle attribute values (e.g., white color, sedan body style, 2020 manufacturing year, etc.). A machine learning model can determine respective embeddings for the vehicle attribute values and the respective embeddings can be concatenated, where the concatenated embeddings represent the user-specified vehicle in one embedding. The system can determine similarity metrics of the concatenated embeddings against reference embeddings. For example, a cosine similarity value can be determined for the concatenated embedding of the user-specified vehicle and the respective reference embeddings. Each similarity metric can represent a measure of similarity between the user-specified vehicle and a given vehicle.Type: GrantFiled: June 8, 2022Date of Patent: January 30, 2024Assignee: Tekion CorpInventors: Nitika Gupta, Ved Surtani
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Publication number: 20240013263Abstract: The online system detects a user interaction between a first user and the online system, and retrieves a set of attributes of the user interaction. Based on the retrieved set of attributes of the user interaction, the online system periodically determines, using a first trained model, a lead score indicative of a likelihood that the user interaction will result in a conversion. If the lead score is higher than a threshold value, the online system determines, using a second trained model, based on attributes of the user interaction between the first user and the online system, and user profile information for the first user, a set of communication parameters to communicate with the first user. The second trained model is trained to select the set of communication parameters to maximize the likelihood of conversion with a least number of communications with the first user associated with the user interaction.Type: ApplicationFiled: July 7, 2022Publication date: January 11, 2024Inventors: Gaurav Gupta, Saikumaar Nagarajan, Nitika Gupta, Ved Surtani
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Patent number: 11763172Abstract: A management system operates in conjunction with entities to provide component recommendations for objects. The management system trains a machine learning model used to generate the component recommendations. The machine learning model is trained based on historical component entries describing components previously provided and identifiers of the components. The management system generates training data by classifying the historical component entries into predetermined component classifications. After the machine learning model is trained, the management system generates a customized recommendation of components for an object based on likelihoods of selection of the predetermined component classifications.Type: GrantFiled: August 16, 2021Date of Patent: September 19, 2023Assignee: Tekion CorpInventors: Jayaprakash Vijayan, Ved Surtani, Nitika Gupta, Pratheek Manjunath Bharadwaj, Indrajit Saha
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Publication number: 20230222365Abstract: A management system operates in conjunction with entities to provide component recommendations for objects. The management system trains a machine learning model used to generate the component recommendations. The machine learning model is trained based on historical component entries describing components previously provided and identifiers of the components. The management system generates training data by classifying the historical component entries into predetermined component classifications. After the machine learning model is trained, the management system generates a customized recommendation of components for an object based on likelihoods of selection of the predetermined component classifications.Type: ApplicationFiled: March 22, 2023Publication date: July 13, 2023Inventors: JAYAPRAKASH VIJAYAN, VED SURTANI, NITIKA GUPTA, PRATHEEK MANJUNATH BHARADWAJ, INDRAJIT SAHA
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Publication number: 20230186250Abstract: A device receives current vehicle data that describes a current state of each of a plurality of components of the vehicle. The device accesses historical data describing prior services previously performed on the vehicle and applies the current vehicle data and the historical vehicle data to a trained machine learning model to obtain a set of recommended services, where the model was trained using labeled training data associated with additional vehicles having a threshold similarity to the vehicle. The machine learning model is trained to output a set of recommended services to be performed for a given vehicle based on inputs of given current vehicle data and given historical vehicle data for the given vehicle. The device outputs for display the set of recommended services to be performed on the vehicle to a user.Type: ApplicationFiled: December 10, 2021Publication date: June 15, 2023Inventors: Nitika Gupta, Ved Surtani, Justin Alexander Chi-Young Hou
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Patent number: 11658917Abstract: A system and a method are disclosed for receiving, by a server, based on input by a user, a request to lock a set of data. Responsively, the server modifies the set of data to be locked, and determines whether an amount of bandwidth required to index the locked data exceeds a threshold. Responsive to determining that the amount of bandwidth exceeds the threshold, the server instructs a secondary server to allocate bandwidth to index a first portion of the locked data. The server indexes a second portion of the locked data in parallel with the secondary server indexing the first portion of the locked data, and generates an index by collating the indexed first and second portions of the locked data. The server receives a search request for a portion of the locked data, and retrieves the portion of the locked data based on referencing the index.Type: GrantFiled: April 9, 2021Date of Patent: May 23, 2023Assignee: Tekion CorpInventors: Satyavrat Mudgil, Justin Hou, Ved Surtani
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Publication number: 20230128497Abstract: A device receives a query from a user associated with a car dealership and applies the query to a first trained machine learning model configured to predict an intent, and to a second trained machine learning model to predict a set of entities. The device generates a normalized representation of the first query that is database language agnostic based on the predicted intent and the predicted set of entities, and translates the normalized representation into a second query having a format compatible with a language of a database of the car dealership. The device fetches data from the database of the car dealership using the second query, and provides the data for display to the user.Type: ApplicationFiled: October 22, 2021Publication date: April 27, 2023Inventors: Jayaprakash Vijayan, Ved Surtani, Nitika Gupta, Malarvizhi Saravanan, Anirudh Saria, Amrutha Dharmaraj
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Publication number: 20230080589Abstract: Systems and methods are disclosed herein for machine-learned vehicle desking operations. A vehicle recommendation system receives a request to determine similarities between vehicles. The request can indicate an identifier of a user-specified vehicle associated with vehicle attribute values (e.g., white color, sedan body style, 2020 manufacturing year, etc.). A machine learning model can determine respective embeddings for the vehicle attribute values and the respective embeddings can be concatenated, where the concatenated embeddings represent the user-specified vehicle in one embedding. The system can determine similarity metrics of the concatenated embeddings against reference embeddings. For example, a cosine similarity value can be determined for the concatenated embedding of the user-specified vehicle and the respective reference embeddings. Each similarity metric can represent a measure of similarity between the user-specified vehicle and a given vehicle.Type: ApplicationFiled: June 8, 2022Publication date: March 16, 2023Inventors: Nitika Gupta, Ved Surtani
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Publication number: 20230060204Abstract: A management system of a plurality of entities generates secondary object recommendations for primary objects being acquired from the entities. The management system generates training data by classifying historical acquisition entries from the entities that describe acquisitions of primary objects and secondary objects with predetermined secondary object classifications. The generated training data is used to train a machine learning model to predict for each predetermined secondary object classification a likelihood of selection of a secondary object associated with the predetermined secondary object classification. Responsive to a primary object being acquired from any one of the plurality of entities, the management system may generate a recommendation for one or more secondary objects to provide with the primary object.Type: ApplicationFiled: August 27, 2021Publication date: March 2, 2023Inventors: Jayaprakash Vijayan, Ved Surtani, Nitika Gupta, Pratheek Manjunath Bharadwaj
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Patent number: 11595446Abstract: A document management system manages documents of an entity. The document management system monitors for entries in a document that are suspicious. Entries in the document are classified by the document management system as a “suspicious entry” or a “non-suspicious entry.” In one embodiment, a suspicious entry is indicative of potentially suspicious activity at the entity.Type: GrantFiled: April 19, 2021Date of Patent: February 28, 2023Assignee: Tekion CorpInventors: Satyavrat Mudgil, Anant Sitaram, Ved Surtani
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Publication number: 20230052423Abstract: A management system operates in conjunction with entities to provide component recommendations for objects. The management system trains a machine learning model used to generate the component recommendations. The machine learning model is trained based on historical component entries describing components previously provided and identifiers of the components. The management system generates training data by classifying the historical component entries into predetermined component classifications. After the machine learning model is trained, the management system generates a customized recommendation of components for an object based on likelihoods of selection of the predetermined component classifications.Type: ApplicationFiled: August 16, 2021Publication date: February 16, 2023Inventors: JAYAPRAKASH VIJAYAN, VED SURTANI, NITIKA GUPTA, PRATHEEK MANJUNATH BHARADWAJ, INDRAJIT SAHA
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Publication number: 20220337628Abstract: A document management system manages documents of an entity. The document management system monitors for entries in a document that are suspicious. Entries in the document are classified by the document management system as a “suspicious entry” or a “non-suspicious entry.” In one embodiment, a suspicious entry is indicative of potentially suspicious activity at the entity.Type: ApplicationFiled: April 19, 2021Publication date: October 20, 2022Inventors: Satyavrat Mudgil, Anant Sitaram, Ved Surtani
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Publication number: 20220329537Abstract: A system and a method are disclosed for receiving, by a server, based on input by a user, a request to lock a set of data. Responsively, the server modifies the set of data to be locked, and determines whether an amount of bandwidth required to index the locked data exceeds a threshold. Responsive to determining that the amount of bandwidth exceeds the threshold, the server instructs a secondary server to allocate bandwidth to index a first portion of the locked data. The server indexes a second portion of the locked data in parallel with the secondary server indexing the first portion of the locked data, and generates an index by collating the indexed first and second portions of the locked data. The server receives a search request for a portion of the locked data, and retrieves the portion of the locked data based on referencing the index.Type: ApplicationFiled: April 9, 2021Publication date: October 13, 2022Inventors: Satyavrat Mudgil, Justin Hou, Ved Surtani
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Publication number: 20220327129Abstract: A system and a method are disclosed for receiving, via a user interface, user input of a first parameter and a second parameter. The system identifies aggregations corresponding to the parameters, the aggregations updated based on input from respective sets of machines, the aggregations being siloed with respect to one another. The system transmits a first query to the first aggregation corresponding to the first parameter, and receives a first response to the first query comprising first data, and transmits a second query to the second aggregation corresponding to the second parameter, and receives a second response to the second query comprising second data. The system integrates the first data and the second data into integrated data, and provides for display, via the user interface, a representation of the integrated data.Type: ApplicationFiled: April 9, 2021Publication date: October 13, 2022Inventors: Satyavrat Mudgil, Justin Hou, Ved Surtani
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Patent number: 11397973Abstract: A management system operates in conjunction with entities to provide service recommendations for objects of users. The management system trains a machine learning model used to generate the service recommendations for the objects. The machine learning model is trained based on historical service entries including descriptions of services previously performed and identifiers used by entities to categorize types of services. The management system generates training data by classifying the historical service entries into predetermined service classifications based on text in the historical service entries. After the machine learning model is trained, the management system generates a recommendation of services for an object based on likelihoods of selection of the predetermined service classifications.Type: GrantFiled: August 16, 2021Date of Patent: July 26, 2022Assignee: Tekion CorpInventors: Jayaprakash Vijayan, Ved Surtani, Nitika Gupta, Amrutha Dharmaraj, Aniruddha Jayant Karajgi
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Patent number: 11386161Abstract: Systems and methods are disclosed herein for machine-learned vehicle desking operations. A vehicle recommendation system receives a request to determine similarities between vehicles. The request can indicate an identifier of a user-specified vehicle associated with vehicle attribute values (e.g., white color, sedan body style, 2020 manufacturing year, etc.). A machine learning model can determine respective embeddings for the vehicle attribute values and the respective embeddings can be concatenated, where the concatenated embeddings represent the user-specified vehicle in one embedding. The system can determine similarity metrics of the concatenated embeddings against reference embeddings. For example, a cosine similarity value can be determined for the concatenated embedding of the user-specified vehicle and the respective reference embeddings. Each similarity metric can represent a measure of similarity between the user-specified vehicle and a given vehicle.Type: GrantFiled: September 10, 2021Date of Patent: July 12, 2022Assignee: Tekion CorpInventors: Nitika Gupta, Ved Surtani