Teradata was granted a patent for managing diverse data analytics frameworks.

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  "signal_subtype": "patentGrant",
  "detected_at": "2026-10-21T15:53:26+00:00",
  "company": {
    "name": "Teradata",
    "domain": "teradata.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G06F 16/2365",
        "label": "Electric digital data processing"
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        "label": "Electric digital data processing"
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    "detail": "In October 2026 Teradata patented reusable analytics components that help data teams run varied analytical workflows across scalable computing environments.",
    "summary": "Teradata was granted a patent for managing diverse data analytics frameworks.",
    "event_at": "2026-10-20",
    "inventors": [
      {
        "name": "David Mueller",
        "status": "unresolved",
        "is_primary": true
      },
      {
        "name": "Sebastian Mariano Salomon",
        "status": "unresolved",
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        "linkedin_url": "https://www.linkedin.com/in/guillaume-koch-6b6a726a"
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      {
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    "tech_area": "software / computing",
    "event_kind": "grant_date",
    "grant_date": "2026-10-20",
    "source_url": "https://patents.google.com/patent/US12769721",
    "cpc_primary": {
      "code": "G06F 16/2365",
      "label": "Electric digital data processing"
    },
    "patent_title": "Management of diverse data analytics frameworks in computing systems",
    "patent_number": "US12769721",
    "uspto_assignee": "Teradata US, Inc.",
    "patent_abstract": "Data Analytics Engines can be provided as a “black-boxed” abstraction to their “users.” This allows a user to mix and match analytical components if their input data matches the input requirement of the engine. Furthermore, by decoupling the Data Analytics Engine creation from the environment, a high degree of process automation, scalability, and improved maintainability can be achieved. As a result, Data Analytic engineers and Data Scientists can create reusable components for other scientists and business users, whereas the users need not know how the Engines are coded or the environment in which their engines will run, but only need to know the input schema of the data.",
    "precision_class": "structural",
    "invention_explanation": "A way to package analytics engines as interchangeable building blocks, so users can combine them when their data meets each block’s requirements.",
    "technologies_mentioned": [
      "data analytics",
      "analytics frameworks",
      "software automation",
      "scalable computing"
    ]
  }
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curl https://signals.autobound.ai/v1/signals/0ae2f27d-4a87-5db0-a8fb-e551e7422e58 \
  -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":"teradata.com","limit":20}'