公开(公告)号：US20240144173A1

公开(公告)日：2024-05-02

申请号：US17977734

申请日：2022-10-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Karuna Ahuja ,  Girija Narlikar ,  Sneha Chandrababu ,  Gowri Rajeev ,  Lan Wang ,  Chakshu Ahuja ,  Sonal Jain

IPC: G06Q10/08 ,  G06K7/10 ,  G06K7/14 ,  G06Q30/02 ,  G06Q30/06

CPC classification number: G06Q10/087 ,  G06K7/10366 ,  G06K7/1417 ,  G06Q30/0202 ,  G06Q30/0623

Abstract: An online concierge system detects acquired items included among an inventory of a customer and identifies one or more candidate available items from the acquired items based on a predicted perishability of each item and a predicted amount of each item that was used. The system retrieves recipes, matches the item(s) likely to be available to a set of recipes based on their ingredients, and identifies any remaining items for each matched recipe not likely to be available. The system retrieves a set of attributes associated with the customer and the set of recipes and computes a suggestion score for each recipe based on the attributes. The system ranks the recipes based on their scores, identifies one or more recipes for suggesting to the customer based on the ranking, and sends the recipe(s) and any remaining items for each recipe to a client device associated with the customer.

公开(公告)号：US12243008B2

公开(公告)日：2025-03-04

申请号：US17977734

申请日：2022-10-31

Applicant: Maplebear Inc.

Inventor： Karuna Ahuja ,  Girija Narlikar ,  Sneha Chandrababu ,  Gowri Rajeev ,  Lan Wang ,  Chakshu Ahuja ,  Sonal Jain

IPC: G06Q10/00 ,  G06K7/10 ,  G06K7/14 ,  G06Q10/087 ,  G06Q30/0202 ,  G06Q30/0601

Abstract: An online concierge system detects acquired items included among an inventory of a customer and identifies one or more candidate available items from the acquired items based on a predicted perishability of each item and a predicted amount of each item that was used. The system retrieves recipes, matches the item(s) likely to be available to a set of recipes based on their ingredients, and identifies any remaining items for each matched recipe not likely to be available. The system retrieves a set of attributes associated with the customer and the set of recipes and computes a suggestion score for each recipe based on the attributes. The system ranks the recipes based on their scores, identifies one or more recipes for suggesting to the customer based on the ranking, and sends the recipe(s) and any remaining items for each recipe to a client device associated with the customer.

公开(公告)号：US20240193657A1

公开(公告)日：2024-06-13

申请号：US18079544

申请日：2022-12-12

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Sneha Chandrababu ,  Karuna Ahuja

IPC: G06Q30/0601

CPC classification number: G06Q30/0617 ,  G06Q30/0633

Abstract: An online concierge system generates an order including multiple items based on unstructured data received from a user through a chat interface instead of manually adding items to the order. The user provides unstructured data to the online concierge system through the chat interface, and the online concierge system extracts an intent from the unstructured data using a natural language process. Based on the intent, the online concierge system identifies a group of items associated with the intent and selects a group of items. The online concierge system generates an order for the user that includes the items comprising the selected group of items.

公开(公告)号：US20240144172A1

公开(公告)日：2024-05-02

申请号：US17977724

申请日：2022-10-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Apurvaa Subramanian ,  Girija Narlikar ,  Chakshu Ahuja ,  Karuna Ahuja ,  Radhika Goel ,  Sneha Chandrababu

IPC: G06Q10/08 ,  G06Q30/02 ,  G06Q30/06

CPC classification number: G06Q10/087 ,  G06Q10/083 ,  G06Q30/0206 ,  G06Q30/0635

Abstract: An online concierge system facilitates a concierge service for ordering, procurement, and delivery of food items from physical retailers. The order fulfillment is based in part on automatically inferring one or more quality metrics, such as remaining shelf-life, associated with perishable food items. A picker shopping on behalf of a customer may capture images of available food items for the order using a picker client device. The images are processed through a machine learning model to infer the one or more quality metrics, and a price is then determined based in part on a dynamic pricing model. The online concierge system communicates with a customer client device to meet quality characteristics and pricing preferences set by the customer. The online concierge system may further facilitate a checkout process for the items obtained by the picker and may facilitate delivery of the items by the picker to the customer.