SAP was granted a patent for AI-driven resource provisioning.

{
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  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-10-30T00:35:29+00:00",
  "company": {
    "name": "SAP",
    "domain": "sap.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G06N 3/08",
        "label": "Computing arrangements based on specific computational models"
      },
      {
        "code": "G06F 9/50",
        "label": "Electric digital data processing"
      }
    ],
    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Artificial Intelligence",
      "Machine Learning",
      "Cloud"
    ],
    "detail": "In October 2026 SAP patented automated cloud and IT-resource allocation that adapts provisioning choices for enterprise jobs.",
    "summary": "SAP was granted a patent for AI-driven resource provisioning.",
    "event_at": "2026-10-27",
    "inventors": [
      {
        "name": "Marcus Ritter",
        "status": "unresolved",
        "is_primary": true
      },
      {
        "name": "Owen Hickey-Moriarty",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Baris Yalcin",
        "status": "unresolved",
        "is_primary": false
      }
    ],
    "tech_area": "artificial intelligence / machine learning",
    "event_kind": "grant_date",
    "grant_date": "2026-10-27",
    "source_url": "https://patents.google.com/patent/US12775840",
    "cpc_primary": {
      "code": "G06N 3/08",
      "label": "Computing arrangements based on specific computational models"
    },
    "patent_title": "Dynamic, automated fulfillment of computer-based resource request provisioning using deep reinforcement learning",
    "patent_number": "US12775840",
    "uspto_assignee": "SAP SE",
    "patent_abstract": "A system and a process for provisioning a job through a trained machine-learning dynamic provisioning agent is provided herein. An input vector representing the job having one or more job components may be received. One or more additional data vectors representing additional job data may be obtained. For the one or more job components respectively, one or more action values corresponding to one or more provisioning options may be calculated based on the one or more additional data vectors. For the one or more job components respectively, one or more provisioning options for the respective one or more job components may be selected based on the corresponding one or more action values. The one or more selected provisioning options corresponding to the respective one or more job components may be aggregated. The aggregated selected provisioning options may be provided.",
    "precision_class": "structural",
    "invention_explanation": "A trained system evaluates each job and its surrounding data, then chooses how to assign the computing resources it needs.",
    "technologies_mentioned": [
      "deep reinforcement learning",
      "resource provisioning",
      "cloud computing",
      "machine learning"
    ]
  }
}

curl https://signals.autobound.ai/v1/signals/0f77d805-cbbb-5e8b-90de-36ab1634e63a \
  -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":"sap.com","limit":20}'