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InstacartPatent grant

Maplebear was granted a patent for matching orders with available pickers.

What happened

In September 2026 Maplebear patented a system for expanding the picker area for less attractive orders in its online grocery fulfillment marketplace.

Source

Abstract

Embodiments relate to order specific expansion of an area that encompasses pickers available for accepting an order placed with an online system. The online system accesses a computer model trained to predict an attractiveness metric for the order and applies the computer model to predict a value of the attractiveness metric for a first order. The online system classifies the first order into a first set or a second set, based on the value of the attractiveness metric and a threshold. Based on the classification, the online system expands over time a size of an area that encompasses a set of pickers available for accepting the first order. The online system causes a device of each picker in the set of available pickers located within the area of the expanded size to display an availability of the first order for acceptance by each picker in the set of available pickers.

patents.google.com/patent/US12749036Read the full source

Extracted by Autobound

From the Signal API record
Signal
Patent grant

What this signalsA new patent often shows where a company is putting its R&D budget.

Grant date
Sep 29, 2026
Inventors
3
Tech area
business methods / CRM / fintech
Patent number
US12749036

The full record

From the Signal API record

People

  • Rahul MakhijaniInventor
  • Pak Tao LeeInventor
  • Shang LiInventor

Details

Primary CPC class
G06Q 10/06316 (Data processing systems for administrative, commercial, financial, managerial or supervisory purposes)
USPTO assignee
Maplebear Inc.
What the invention does
A model scores how appealing an order is to pickers and expands the eligible pickup area when the score falls below a set threshold.

Topics and mentions

Tags

  • Intellectual Property
  • Research & Development
  • Machine Learning
  • Logistics / Supply Chain
  • eCommerce

Technologies named

  • online marketplaces
  • machine learning
  • order fulfillment
  • workforce optimization

Extraction

Detected
Sep 30, 2026
signal_type
patents-company
signal_subtype
patentGrant

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This page shows a preview. The full patents-company record in the Signal API and MCP can also have these 8 fields. Some fields are empty for some signals.

Company

  • linkedin_urlValue in the API
  • industriesValue in the API
  • employee_count_lowValue in the API
  • employee_count_highValue in the API
  • revenueValue in the API
  • descriptionValue in the API

Signal

  • signal_nameValue in the API
  • associationValue in the API
Show the full JSONThe record on this page and the API request

GET /v1/signals/2da20f5e-4d92-5332-bd5f-a3ae846cf59b returns this record as JSON. POST /v1/companies/enrich returns every signal for instacart.com.

{
  "signal_id": "2da20f5e-4d92-5332-bd5f-a3ae846cf59b",
  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-09-30T17:21:34+00:00",
  "company": {
    "name": "Instacart",
    "domain": "instacart.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G06Q 10/06316",
        "label": "Data processing systems for administrative, commercial, financial, managerial or supervisory purposes"
      }
    ],
    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Machine Learning",
      "Logistics / Supply Chain",
      "eCommerce"
    ],
    "detail": "In September 2026 Maplebear patented a system for expanding the picker area for less attractive orders in its online grocery fulfillment marketplace.",
    "summary": "Maplebear was granted a patent for matching orders with available pickers.",
    "event_at": "2026-09-29",
    "inventors": [
      {
        "name": "Rahul Makhijani",
        "status": "unresolved",
        "is_primary": true
      },
      {
        "name": "Pak Tao Lee",
        "status": "resolved",
        "is_primary": false,
        "linkedin_url": "https://www.linkedin.com/in/leepaktao"
      },
      {
        "name": "Shang Li",
        "status": "resolved",
        "is_primary": false,
        "linkedin_url": "https://www.linkedin.com/in/shang-li-columbia"
      }
    ],
    "tech_area": "business methods / CRM / fintech",
    "event_kind": "grant_date",
    "grant_date": "2026-09-29",
    "source_url": "https://patents.google.com/patent/US12749036",
    "cpc_primary": {
      "code": "G06Q 10/06316",
      "label": "Data processing systems for administrative, commercial, financial, managerial or supervisory purposes"
    },
    "patent_title": "Order-specific expansion of an area encompassing pickers available for accepting orders placed with an online system",
    "patent_number": "US12749036",
    "uspto_assignee": "Maplebear Inc.",
    "patent_abstract": "Embodiments relate to order specific expansion of an area that encompasses pickers available for accepting an order placed with an online system. The online system accesses a computer model trained to predict an attractiveness metric for the order and applies the computer model to predict a value of the attractiveness metric for a first order. The online system classifies the first order into a first set or a second set, based on the value of the attractiveness metric and a threshold. Based on the classification, the online system expands over time a size of an area that encompasses a set of pickers available for accepting the first order. The online system causes a device of each picker in the set of available pickers located within the area of the expanded size to display an availability of the first order for acceptance by each picker in the set of available pickers.",
    "precision_class": "structural",
    "invention_explanation": "A model scores how appealing an order is to pickers and expands the eligible pickup area when the score falls below a set threshold.",
    "technologies_mentioned": [
      "online marketplaces",
      "machine learning",
      "order fulfillment",
      "workforce optimization"
    ]
  }
}

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