Gusto was granted a patent for machine-learning resource allocation.

{
  "signal_id": "38378b50-9676-5cfa-a368-6e42d41904aa",
  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-09-16T04:15:04+00:00",
  "company": {
    "name": "Gusto",
    "domain": "gusto.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G06N 20/00",
        "label": "Computing arrangements based on specific computational models"
      }
    ],
    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Artificial Intelligence",
      "Machine Learning",
      "Database"
    ],
    "detail": "In August 2026 Gusto patented predictive models for allocating centralized database resources and anticipating issues across payroll and workforce-management records.",
    "summary": "Gusto was granted a patent for machine-learning resource allocation.",
    "event_at": "2026-08-11",
    "inventors": [
      {
        "name": "Christian Franklin Hillson",
        "status": "unresolved",
        "is_primary": true
      },
      {
        "name": "Jacques Robert Caspi",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Andrew Collins Bessey",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Lilly Anne Pieper",
        "status": "resolved",
        "is_primary": false,
        "linkedin_url": "https://www.linkedin.com/in/lillyannepieper"
      },
      {
        "name": "Ryan David Kappedal",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Jasmine Walker Motupalli",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Addison Woodford Bohannon",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Rebecca Alice Carter",
        "status": "unresolved",
        "is_primary": false
      }
    ],
    "tech_area": "artificial intelligence / machine learning",
    "event_kind": "grant_date",
    "grant_date": "2026-08-11",
    "source_url": "https://patents.google.com/patent/US12705542",
    "cpc_primary": {
      "code": "G06N 20/00",
      "label": "Computing arrangements based on specific computational models"
    },
    "patent_title": "Machine learned resource allocation models for centralized database predictions",
    "patent_number": "US12705542",
    "uspto_assignee": "Gusto, Inc.",
    "patent_abstract": "A central database system trains and applies machine-learned models based on characteristics of one or more entities associated with the central database system. For instance, the central database system trains a machine-learned model configured to identify issues a target entity is likely to encounter based on training data identifying characteristics of historical entities and issues faced by the historical entities. Likewise, the central database system trains machine-learned models configured to predict actions that entities are likely to take in the future, and resources required to take those actions. The central database system can then perform one or more proactive actions or make one or more recommendations based on the predicted issues, the predicted future actions, and the predicted required resources.",
    "precision_class": "structural",
    "invention_explanation": "A system that learns from past entities and problems to predict what a new entity may need and assign database resources accordingly.",
    "technologies_mentioned": [
      "machine learning",
      "predictive analytics",
      "centralized databases"
    ]
  }
}

curl https://signals.autobound.ai/v1/signals/38378b50-9676-5cfa-a368-6e42d41904aa \
  -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":"gusto.com","limit":20}'