Block, Inc.

Marvin Balaoro

Brett Andler

Yenliang Chen

Jeremy Martin

Rowan Schultz

Cory Douthat

Mani Razaghi Kashani

Nicholas Kunst

Steven Stallion

Nikolaj Leschly

Mani Razaghi

Nicholas Burrows

Isreal Blagdan

Joshua Boilard

Nicholas Slaney

Michael Alan MacLennan

Jade Fernandez

Patrick Willett

Nika Torab

A brick-and-mortar (BAM) store control system uses sensors and wireless transceivers to track customers, merchant representatives, devices, and/or objects within a BAM store area. The system can identify and track product and/or service inventory within the BAM store area and/or in individual's personal inventories, for instance by detecting movements of objects by individuals in sensor data. The system can generate inventory replenishment schedules, for instance based on inventory quantity patterns. The system can provide recommendations to customers and/or merchants, for example recommending products that customers have interacted with. The system can identify individuals and/or objects using a machine learning algorithm, which can learn based on feedback. The system can generate temporary identifiers for unrecognized individuals or objects, which it can merge or convert into long-term identifiers as more information is received. The system can recognize sensitive information based on secure identifiers generated based on the sensitive information.

Learning for individual detection in brick and mortar store based on sensor data and feedback

A transaction system receives a card into a slot between a plurality of surfaces (e.g., a first surface and a second surface) of a housing. The transaction system detects, using at least one detector, that a storage medium of the card faces the one of the plurality of surfaces at a first time while the card is received by the slot. Between the first time and a second time (that is after the first time), the transaction system prepares one of a plurality of reader interfaces (e.g., a first reader interface or a second reader interface) to read information from the storage medium in response to the at least one detector detecting that the storage medium of the card is facing the one of the plurality of surfaces. At the second time, the one of the plurality of reader interfaces reads the information from the storage medium of the card.

Reader device with a plurality of reader interfaces

Point of sale (POS) systems and methods are described. A POS device includes a housing with a payment instrument reader. The payment instrument reader reads payment instrument information from a payment instrument in response to receipt of the payment instrument at a read area of the housing. The POS device includes a first second fastening mechanism that secures the housing to a mount that is coupled to a surface of the environment. The POS device includes a cradle of the housing that receives a mobile computing device. The POS device includes a first fastening mechanism that secures the mobile computing device within the cradle. The POS device includes a connector coupled to the payment instrument reader and extending into the cradle. The connector is configured to couple to the mobile computing device in the cradle, to convey the payment instrument information from the payment instrument reader to the mobile computing device.

Point of sale device for mobile computing device

Automatic inventory tracking in brick and mortar store based on sensor data

A point of sale (POS) device includes a nest portion and a cradle portion. The nest portion includes one or more payment card or near field communication (NFC) readers. The cradle portion couples to differently-sized interchangeable frames, which in turn help secure a mobile computing device to the cradle portion of the POS device. The mobile computing device is connected via a connector to the rest of the POS device. Payment card information read by the readers is conveyed to the mobile computing device over the connector for processing. The POS device may also include tamper detection circuitry.

Point of sale device with cradle for computing device

Point of sale device with cradle for mobile computing device

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San Francisco, CA, United States of America

Marvin Balaoro