Writer was granted a patent for knowledge-graph-based text generation.

{
  "signal_id": "4f3fffc2-d538-5201-ba32-431a32b5a34d",
  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-09-23T15:07:10+00:00",
  "company": {
    "name": "Writer",
    "domain": "writer.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G06F 40/40",
        "label": "Electric digital data processing"
      },
      {
        "code": "G06F 16/33295",
        "label": "Electric digital data processing"
      },
      {
        "code": "G06F 16/345",
        "label": "Electric digital data processing"
      },
      {
        "code": "G06F 40/30",
        "label": "Electric digital data processing"
      },
      {
        "code": "G06N 5/04",
        "label": "Computing arrangements based on specific computational models"
      }
    ],
    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Artificial Intelligence",
      "Language Technology",
      "Enterprise Software"
    ],
    "detail": "In September 2026 Writer patented a language-generation approach for producing more informed text in enterprise content and software applications.",
    "summary": "Writer was granted a patent for knowledge-graph-based text generation.",
    "event_at": "2026-09-22",
    "inventors": [
      {
        "name": "Waseem AlShikh",
        "status": "resolved",
        "is_primary": true,
        "linkedin_url": "https://www.linkedin.com/in/waseemalshikh"
      }
    ],
    "tech_area": "software / computing",
    "event_kind": "grant_date",
    "grant_date": "2026-09-22",
    "source_url": "https://patents.google.com/patent/US12743588",
    "cpc_primary": {
      "code": "G06F 40/40",
      "label": "Electric digital data processing"
    },
    "patent_title": "Natural language generation using knowledge graph incorporating textual summaries",
    "patent_number": "US12743588",
    "uspto_assignee": "Writer, Inc.",
    "patent_abstract": "Techniques relate to receiving a natural-language textual sequence representing the textual input; retrieving, from a knowledge graph associated with the domain: a first textual passage based on a first ranking regarding the natural-language textual sequence, a first textual summary associated with the first textual passage, a second textual passage based on a first ranking with respect to a comparison of the second textual passage and the natural-language textual sequence a second textual summary associated with the second textual passage, and a third textual summary based on a second ranking regarding the natural-language textual sequence; obtaining the textual output in response to the textual input from a language model by providing input to the language model using the natural-language textual sequence, the first textual passage, the first textual summary, the second textual passage, the second textual summary, and the third textual summary; and providing an output based on the textual output.",
    "precision_class": "structural",
    "invention_explanation": "A method that searches a subject-specific knowledge graph for relevant passages and summaries, then uses them to guide the creation of natural-language output.",
    "technologies_mentioned": [
      "natural language generation",
      "knowledge graphs",
      "text summarization",
      "language processing"
    ]
  }
}

curl https://signals.autobound.ai/v1/signals/4f3fffc2-d538-5201-ba32-431a32b5a34d \
  -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":"writer.com","limit":20}'