U.S. Bank was granted a patent for improved document matching.

{
  "signal_id": "95f7f363-923a-523b-b269-cac157c887d5",
  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-10-30T00:32:26+00:00",
  "company": {
    "name": "U.S. Bank",
    "domain": "usbank.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G06F 16/94",
        "label": "Electric digital data processing"
      },
      {
        "code": "G06F 40/30",
        "label": "Electric digital data processing"
      }
    ],
    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Data Management",
      "Software"
    ],
    "detail": "In October 2026 U.S. Bank patented a data-processing method for identifying duplicate documents in banking records and other digital document repositories.",
    "summary": "U.S. Bank was granted a patent for improved document matching.",
    "event_at": "2026-10-27",
    "inventors": [
      {
        "name": "Christopher Davis",
        "status": "unresolved",
        "is_primary": true
      },
      {
        "name": "Christopher Ziolkowski",
        "status": "unresolved",
        "is_primary": false
      }
    ],
    "tech_area": "software / computing",
    "event_kind": "grant_date",
    "grant_date": "2026-10-27",
    "source_url": "https://patents.google.com/patent/US12775668",
    "cpc_primary": {
      "code": "G06F 16/94",
      "label": "Electric digital data processing"
    },
    "patent_title": "Enhanced string match matrix generation",
    "patent_number": "US12775668",
    "uspto_assignee": "U.S. Bank National Association",
    "patent_abstract": "A method for remediating duplication errors associated with first and second documents includes obtaining a first document and a second document, generating a corresponding first document string set and a second document string set, generating a second document string subset that is a proper subset of the second document string set, dividing the second document string subset into second document substring, transforming the second document substrings into a synthetic substring set, converting the first document string set into first document embeddings in vector space, converting the synthetic substrings into synthetic embeddings, generate a closest embedding set of one or more first document embeddings, generating, using a respective one of the closest embedding sets and a linking string generator, a linking string defining an association between the respective substring and one or more respective first document portions, and generating a string match matrix data.",
    "precision_class": "structural",
    "invention_explanation": "A way to break documents into smaller text pieces and create variations of those pieces so similar or duplicated records can be matched more reliably.",
    "technologies_mentioned": [
      "document matching",
      "text processing",
      "data deduplication"
    ]
  }
}

curl https://signals.autobound.ai/v1/signals/95f7f363-923a-523b-b269-cac157c887d5 \
  -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":"usbank.com","limit":20}'