Google Patents: Search

curl --request GET \
  --url https://api.perceptlayer.com/v1/google-patents/search \
  --header 'X-API-Key: <api-key>'

import requests

url = "https://api.perceptlayer.com/v1/google-patents/search"

headers = {"X-API-Key": "<api-key>"}

response = requests.get(url, headers=headers)

print(response.text)

const options = {method: 'GET', headers: {'X-API-Key': '<api-key>'}};

fetch('https://api.perceptlayer.com/v1/google-patents/search', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

const url = 'https://api.perceptlayer.com/v1/google-patents/search';
const options = {method: 'GET', headers: {'X-API-Key': '<api-key>'}};

fetch(url, options)
  .then(res => res.json())
  .then(json => console.log(json))
  .catch(err => console.error(err));

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.perceptlayer.com/v1/google-patents/search"

	req, _ := http.NewRequest("GET", url, nil)

	req.Header.Add("X-API-Key", "<api-key>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.perceptlayer.com/v1/google-patents/search",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
  CURLOPT_HTTPHEADER => [
    "X-API-Key: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

require 'uri'
require 'net/http'

url = URI("https://api.perceptlayer.com/v1/google-patents/search")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Get.new(url)
request["X-API-Key"] = '<api-key>'

response = http.request(request)
puts response.read_body

HttpResponse<String> response = Unirest.get("https://api.perceptlayer.com/v1/google-patents/search")
  .header("X-API-Key", "<api-key>")
  .asString();

{
  "endpoint": "google-patents.search",
  "params": {
    "q": "machine learning"
  },
  "response": {
    "success": true,
    "data": {
      "total_results": 122797,
      "total_pages": 99,
      "current_page": 1,
      "many_results": false,
      "patents": [
        {
          "patent_id": "patent/US12438891B1/en",
          "rank": 0,
          "title": "Anomaly detection based on ensemble machine learning model",
          "snippet": "accessing the entity profile to read the plurality of features scores for the entity; processing the plurality of feature scores for the entity, accessed from the entity profile, by using a plurality of machine-learning models; generating a…",
          "publication_number": "US12438891B1",
          "language": "en",
          "dates": {
            "priority": "2015-08-31",
            "filing": "2022-02-18",
            "grant": "2025-10-07",
            "publication": "2025-10-07"
          },
          "inventor": "Sudhakar Muddu",
          "assignee": "Splunk Inc.",
          "thumbnail": "60x80/US12438891B1/US12438891-20251007-D00000.png",
          "pdf": "",
          "family_status": [
            {
              "country": "US",
              "status": "ACTIVE"
            }
          ]
        },
        {
          "patent_id": "patent/US12518214B2/en",
          "rank": 1,
          "title": "Distributed machine learning systems including generation of synthetic data",
          "snippet": "wherein the machine learning model instructions comprise at least one of supervised machine learning instructions, unsupervised machine learning instructions, or machine learning clustering instructions. 15 . The system of claim 1 , wherein…",
          "publication_number": "US12518214B2",
          "language": "en",
          "dates": {
            "priority": "2016-07-18",
            "filing": "2023-04-21",
            "grant": "2026-01-06",
            "publication": "2026-01-06"
          },
          "inventor": "Christopher W. Szeto",
          "assignee": "Nantomics, Llc",
          "thumbnail": "60x80/US12518214B2/US12518214-20260106-D00000.png",
          "pdf": "",
          "family_status": [
            {
              "country": "WO",
              "status": "NOT_ACTIVE"
            },
            {
              "country": "EP",
              "status": "NOT_ACTIVE"
            },
            {
              "country": "US",
              "status": "ACTIVE"
            }
          ]
        },
        {
          "patent_id": "patent/JP7607720B2/en",
          "rank": 2,
          "title": "Cyber threat defense system that uses machine learning models to protect email …",
          "snippet": "one or more first machine learning models trained on normal behavior of email and user activity associated with the email system; a cyber-threat module having one or more second machine learning models trained on cyber-threats in the email …",
          "publication_number": "JP7607720B2",
          "language": "en",
          "dates": {
            "priority": "2018-02-20",
            "filing": "2023-09-21",
            "grant": "2024-12-27",
            "publication": "2024-12-27"
          },
          "inventor": "ダン マシュー",
          "assignee": "ダークトレース リミテッド",
          "thumbnail": "1b/50/29/fa98ef7b352324/0007607720000001.png",
          "pdf": "a8/70/e5/da2bef3a38d91c/JP7607720B2.pdf",
          "family_status": [
            {
              "country": "EP",
              "status": "ACTIVE"
            },
            {
              "country": "US",
              "status": "ACTIVE"
            },
            {
              "country": "JP",
              "status": "ACTIVE"
            }
          ]
        }
      ],
      "cached": false,
      "response_time_ms": 731
    }
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
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  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>"
  }
}