PayPal was granted a patent for adaptive graph-based machine learning.

{
  "signal_id": "364c1a49-d5a0-58d9-b759-2c0890d26064",
  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-09-30T17:20:53+00:00",
  "company": {
    "name": "PayPal",
    "domain": "paypal.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G06N 5/027",
        "label": "Computing arrangements based on specific computational models"
      },
      {
        "code": "G06N 5/022",
        "label": "Computing arrangements based on specific computational models"
      },
      {
        "code": "G06Q 20/3678",
        "label": "Data processing systems for administrative, commercial, financial, managerial or supervisory purposes"
      },
      {
        "code": "G06Q 20/4016",
        "label": "Data processing systems for administrative, commercial, financial, managerial or supervisory purposes"
      },
      {
        "code": "G06Q 2220/00",
        "label": "Data processing systems for administrative, commercial, financial, managerial or supervisory purposes"
      }
    ],
    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Artificial Intelligence",
      "Machine Learning",
      "Data Science"
    ],
    "detail": "In September 2026 PayPal patented an AI framework for analyzing changing, irregular relationships in data networks used in financial and digital platforms.",
    "summary": "PayPal was granted a patent for adaptive graph-based machine learning.",
    "event_at": "2026-09-29",
    "inventors": [
      {
        "name": "Yanfei Dong",
        "status": "unresolved",
        "is_primary": true
      }
    ],
    "tech_area": "artificial intelligence / machine learning",
    "event_kind": "grant_date",
    "grant_date": "2026-09-29",
    "source_url": "https://patents.google.com/patent/US12748988",
    "cpc_primary": {
      "code": "G06N 5/027",
      "label": "Computing arrangements based on specific computational models"
    },
    "patent_title": "Dynamic prototype learning framework for non-homophilous graphs",
    "patent_number": "US12748988",
    "uspto_assignee": "PayPal, Inc.",
    "patent_abstract": "Methods and systems are presented for providing a framework for analyzing graphs that exhibit non-homophilous behavior. Under the framework, a structural analysis and a feature-based analysis will be performed on a sequence of graphs. When performing the feature-based analysis, various features are extracted from each node in the sequence of graphs, and clusters of nodes are identified from each graph based on the features. A set of evolving prototypes is generated to represent evolving characteristics of the clusters of nodes, and a set of persistent prototypes is generated to represent persistent characteristics of the clusters of nodes. Information derived from the structural analysis of the graphs, the set of evolving prototypes, and the set of persistent prototypes are embedded within the nodes of the graphs. The embedded information is then used to classify the nodes.",
    "precision_class": "structural",
    "invention_explanation": "A method that groups connected data points by their characteristics and continually updates representative patterns as the network changes.",
    "technologies_mentioned": [
      "graph machine learning",
      "AI clustering",
      "dynamic prototypes",
      "network analysis"
    ]
  }
}

curl https://signals.autobound.ai/v1/signals/364c1a49-d5a0-58d9-b759-2c0890d26064 \
  -H "X-API-KEY: $AUTOBOUND_API_KEY"

curl -X POST https://signals.autobound.ai/v1/companies/enrich \
  -H "X-API-KEY: $AUTOBOUND_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain":"paypal.com","limit":20}'