Salesforce was granted a patent for neural-network recommendation models.

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  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-10-14T15:53:20+00:00",
  "company": {
    "name": "Salesforce",
    "domain": "salesforce.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G06N 3/08",
        "label": "Computing arrangements based on specific computational models"
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    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Artificial Intelligence",
      "Machine Learning",
      "Enterprise Software"
    ],
    "detail": "In October 2026 Salesforce patented machine-learning technology for improving personalized recommendations in customer and business software.",
    "summary": "Salesforce was granted a patent for neural-network recommendation models.",
    "event_at": "2026-10-13",
    "inventors": [
      {
        "name": "Regunathan Radhakrishnan",
        "status": "resolved",
        "is_primary": true,
        "linkedin_url": "https://www.linkedin.com/in/regu-radhakrishnan-4b76bb1"
      },
      {
        "name": "Zachary Alexander",
        "status": "unresolved",
        "is_primary": false
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      {
        "name": "Sitaram Asur",
        "status": "resolved",
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      {
        "name": "Shashank Harinath",
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        "linkedin_url": "https://www.linkedin.com/in/shashankharinath"
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      {
        "name": "Na Cheng",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Shiva Kumar Pentyala",
        "status": "resolved",
        "is_primary": false,
        "linkedin_url": "https://www.linkedin.com/in/shiva-pentyala"
      }
    ],
    "tech_area": "artificial intelligence / machine learning",
    "event_kind": "grant_date",
    "grant_date": "2026-10-13",
    "source_url": "https://patents.google.com/patent/US12762400",
    "cpc_primary": {
      "code": "G06N 3/08",
      "label": "Computing arrangements based on specific computational models"
    },
    "patent_title": "Systems and methods for neural network based recommender models",
    "patent_number": "US12762400",
    "uspto_assignee": "Salesforce, Inc.",
    "patent_abstract": "Embodiments described herein provide A method for training a neural network based model. The methods include receiving a training dataset with a plurality of training samples, and those samples are encoded into representations in feature space. A positive sample is determined from the raining dataset based on a relationship between the given query and the positive sample in feature space. For a given query, a positive sample from the training dataset is selected based on a relationship between the given query and the positive sample in a feature space. One or more negative samples from the training dataset that are within a reconfigurable distance to the positive sample in the feature space are selected, and a loss is computed based on the positive sample and the one or more negative samples. The neural network is trained based on the loss.",
    "precision_class": "structural",
    "invention_explanation": "A training method that represents queries and examples as points in a feature space, then teaches the neural network by pairing each query with a closely related positive example.",
    "technologies_mentioned": [
      "neural networks",
      "recommender systems",
      "machine learning",
      "feature embeddings"
    ]
  }
}

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