Tekion, Inc.

Other

Jayaprakash Vijayan

Gurusankar Sankararaman

Ved Surtani

Nitika Gupta

Sigmundo Bautista

Anand Ramakotti

Amrutha Dharmaraj

Anant Sitaram

Justin Alexander Chi-Young Hou

Jagdish Mohanlal Patel

Robert Kennedy Manoharan

Pratheek Manjunath Bharadwaj

Indrajit Saha

Anirudh Saria

Malarvizhi Saravanan

Aniruddha Jayant Karajgi

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.

Machine learning-implemented chat bot database query system for multi-format database queries

A management system operates in conjunction with an automotive dealership to improve customer engagement with the automotive dealership. The management system creates customer profiles of the automotive dealership systems' customers using features of the customers obtained via various sources. The management system assigns a customer category to a customer based on the features included in the customer profile and may generate a customized recommendation of a product and/or service for the customer to purchase at the dealership based at least in part on the customer category.

Customer categorization and customized recommendations for automotive retail

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.

Providing component recommendation using machine learning

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.

Generating training data for machine learning model for providing recommendations for services

In one aspect, a computerized method useful for three-dimensional (3D) model data rendering and information capturing during a vehicle inspection check-in process for service comprising includes the step of providing a vehicle for a check-in inspection. The computerized method includes the step of obtaining a vehicle identification number (VIN) of the vehicle. The computerized method includes the step of, based on the VIN of the vehicle, obtaining a 3D vehicle model data. The 3D vehicle model data matches a type of the vehicle. The 3D vehicle model data is generated from a manufacturer's three-dimensional (3D) computer-aided design (CAD) model data of the type of the vehicle.

3D vehicle model data capturing and retrieving for vehicle inspection, service and maintenance

Vehicle data acquisition device

In one aspect, a computerized method useful for implementing location awareness a vehicle coupled with an on-board diagnostics (OBD) pass-through dongle includes the step of providing a plurality of wireless personal area network (WPAN) beacons, wherein plurality of WPAN beacons transmits a low-energy WPAN signal. The computerized method includes the step of pre-mapping a plurality of subareas in the area with a set of signal attributes for each WPAN beacon of the plurality of WPAN beacons. The computerized method includes the step of coupling a vehicle with an OBD pass-through dongle, wherein the OBD pass-through dongle comprises a Low-Power Wide-Area Network (LPWAN) module, and wherein the OBD pass-through dongle comprises a WPAN module. The computerized method includes the step of, with the WPAN module, receiving one or more WPAN signals from the plurality of WPAN beacons.

Methods and systems of an on-board diagnostics pass-through dongle

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Dublin, CA, United States of America

Jayaprakash Vijayan