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EverpurePatent grant

Everpure was granted a patent for faster AI data delivery.

What happened

In September 2026 Everpure patented a system for preparing and distributing model-ready datasets across GPU clusters, supporting large-scale AI workloads.

Source

Abstract

A method is disclosed for managing transformed datasets in a compute cluster environment. The method includes identifying, based on one or more machine learning models to be executed on a compute cluster comprising a plurality of GPU servers, one or more transformations to apply to a dataset. The method further includes generating a transformed dataset based on the one or more transformations, storing the transformed dataset, receiving a request to transmit the transformed dataset to at least one GPU server of the plurality of GPU servers, and, responsive to the request, transmitting the stored transformed dataset to the at least one GPU server without re-performing the one or more transformations on the dataset.

patents.google.com/patent/US12737356Read the full source

Extracted by Autobound

From the Signal API record
Signal
Patent grant

What this signalsA new patent often shows where a company is putting its R&D budget.

Grant date
Sep 15, 2026
Inventors
4
Tech area
software / computing
Patent number
US12737356

The full record

From the Signal API record

People

  • Brian GoldInventor
  • Emily WatkinsInventor
  • Ivan JibajaInventor
  • Igor OstrovskyInventor
  • Roy KimInventor

Details

Primary CPC class
G06F 16/24534 (Electric digital data processing)
USPTO assignee
EVERPURE, INC.
What the invention does
A method that transforms data once, stores the result, and sends the prepared version to the GPU servers that need it.

Topics and mentions

Tags

  • Intellectual Property
  • Research & Development
  • Artificial Intelligence
  • Cloud
  • Data Management

Technologies named

  • artificial intelligence
  • GPU clusters
  • distributed storage
  • data transformation

Extraction

Detected
Sep 20, 2026
signal_type
patents-company
signal_subtype
patentGrant

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This page shows a preview. The full patents-company record in the Signal API and MCP can also have these 8 fields. Some fields are empty for some signals.

Company

  • linkedin_urlValue in the API
  • industriesValue in the API
  • employee_count_lowValue in the API
  • employee_count_highValue in the API
  • revenueValue in the API
  • descriptionValue in the API

Signal

  • signal_nameValue in the API
  • associationValue in the API
Show the full JSONThe record on this page and the API request

GET /v1/signals/de130570-5310-5a85-90b4-2fc166162646 returns this record as JSON. POST /v1/companies/enrich returns every signal for everpuredata.com.

{
  "signal_id": "de130570-5310-5a85-90b4-2fc166162646",
  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-09-20T17:58:13+00:00",
  "company": {
    "name": "Everpure",
    "domain": "everpuredata.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G06F 16/24534",
        "label": "Electric digital data processing"
      },
      {
        "code": "G06F 3/06",
        "label": "Electric digital data processing"
      },
      {
        "code": "G06F 3/061",
        "label": "Electric digital data processing"
      },
      {
        "code": "G06F 3/0629",
        "label": "Electric digital data processing"
      },
      {
        "code": "G06F 3/0647",
        "label": "Electric digital data processing"
      }
    ],
    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Artificial Intelligence",
      "Cloud",
      "Data Management"
    ],
    "detail": "In September 2026 Everpure patented a system for preparing and distributing model-ready datasets across GPU clusters, supporting large-scale AI workloads.",
    "summary": "Everpure was granted a patent for faster AI data delivery.",
    "event_at": "2026-09-15",
    "inventors": [
      {
        "name": "Brian Gold",
        "status": "unresolved",
        "is_primary": true
      },
      {
        "name": "Emily Watkins",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Ivan Jibaja",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Igor Ostrovsky",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Roy Kim",
        "status": "unresolved",
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      }
    ],
    "tech_area": "software / computing",
    "event_kind": "grant_date",
    "grant_date": "2026-09-15",
    "source_url": "https://patents.google.com/patent/US12737356",
    "cpc_primary": {
      "code": "G06F 16/24534",
      "label": "Electric digital data processing"
    },
    "patent_title": "Efficient data delivery for artificial intelligence systems in distributed storage environments",
    "patent_number": "US12737356",
    "uspto_assignee": "EVERPURE, INC.",
    "patent_abstract": "A method is disclosed for managing transformed datasets in a compute cluster environment. The method includes identifying, based on one or more machine learning models to be executed on a compute cluster comprising a plurality of GPU servers, one or more transformations to apply to a dataset. The method further includes generating a transformed dataset based on the one or more transformations, storing the transformed dataset, receiving a request to transmit the transformed dataset to at least one GPU server of the plurality of GPU servers, and, responsive to the request, transmitting the stored transformed dataset to the at least one GPU server without re-performing the one or more transformations on the dataset.",
    "precision_class": "structural",
    "invention_explanation": "A method that transforms data once, stores the result, and sends the prepared version to the GPU servers that need it.",
    "technologies_mentioned": [
      "artificial intelligence",
      "GPU clusters",
      "distributed storage",
      "data transformation"
    ]
  }
}

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