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Unsere
Plattform

Die Plattform für automatisierte Dokumentenverarbeitung

Wir bieten den Zugang zu einer der leistungsstärksten KI-Technologien zur Dokumentenautomatisierung, die auf hunderttausenden von Dokumenten aus der ganzen Welt trainiert wurde.
Die natif.ai Plattform gibt Zugang zu Basistechnologien wie unserer Deep-OCR, verschiedensten vorgefertigten Use-Cases und Dokumenten-Workflows. Alles ist, dank der Rest-API, einfach mit wenigen Klicks in bestehende Prozesse zu implementieren.

Robust Reading

Unsere Deep-OCR liest auch Dokumente mit niedriger Qualität und kann speziell an schwierige Use Cases angepasst werden.

Plug & Play

Dank Rest API sind unsere KI-Modelle schnell in bestehende Systeme integriert.

Datenschutz

Wir sind zu 100 % DSGVO- und Schrems II-konform. Wir verarbeiten die Daten auf unseren Servern und verzichten auf Dienstleister.

KI Boost

Unsere KI-Modelle versetzen Ihre Software direkt in die Lage Dokumente zu automatisieren.

Individuelle Klassifizierung

Eigene Dokumenten-Klassen definieren und mit wenigen Beispielen die KI trainieren.

Positionsdaten

Neben klassischen Kopfdaten kann unsere KI auch Positionsdaten extrahieren.

Geschwindigkeit

Da unsere KI auf GPUs läuft, verarbeiten wir Dokumente in Echtzeit (normalerweise weniger als 1 Sekunde pro Seite).

Schwarm Wissen

Unsere KI profitiert von dem Feedback all unserer Kunden, somit müssen Probleme nicht von jedem aufs Neue gelöst werden.

Zugriff auf verschiedene Dokumententypen

Auf unserer Plattform geben wir Zugang zu verschiedensten Technologien zur Automatisierung von Dokumentenprozessen.
Egal ob Rechnungs-Automatisierung, Handschriften-Erkennung oder Ausweisdokumente, es genügen wenige Clicks um mit der Automatisierung zu starten.

Eigene Dokumenten-Klassifizierung

In sechs einfachen Schritten können Sie ein eigenes Modell zur Dokumenten-Klassifizierung trainieren.
Egal welche Dokumenten-Klassen für Sie relevant sind, Sie können mit nur wenigen Beispielen Klassifizierungsmodelle trainieren und diese einfach über die Rest-API in bestehende Prozesse implementieren.

Individuelles verbessern der KI

Unsere Modelle für den eigenen Bedarf weiterentwickeln? Kein Problem! In vier einfachen Schritten können unsere Dokumenten-Typen auf die individuellen Bedürfnisse trainiert werden, um immer die höchste Automatisierungs-Quote zu gewährleisten.

Rest-API

Alle Technologien sind einfach über die Rest-API in bestehende Prozesse zu integrieren.
Wir bieten fertige Integrationen in den gängigen Programmiersprachen. Die Schlüsselinformationen werden als strukturiertes JSON-Format über die Schnittstelle zur Verfügung gestellt. Zu jedem Datenpunkt liefert diese zudem die exakte Position auf dem Dokument, den Wert sowie das Konfidenz-Level. Zusätzlich zur JSON-Datei liefern wir eine PDF/A-Datei inklusive des Text-Layers.
{
  "processing_id": "bfb819fb-b193-42fa-ad19-8ad33aa8831b",
  "available_results": [
    "pdf",
    "ocr",
    "page-images",
    "hocr",
    "language",
    "thumbnail"
  ],
  "pdf": "/processing/results/bfb819fb-b193-42fa-ad19-8ad33aa8831b/pdf",
  "ocr": {
    "pages": [
      {
        "width": 2380,
        "height": 3368,
        "bboxes": [
          {
            "id": 1,
            "x1": 82,
            "y1": 333,
            "x2": 102,
            "y2": 351,
            "text": "a",
            "text_entropy": 0.58203125
          },
          {
            "id": 2,
            "x1": 132,
            "y1": 1508,
            "x2": 551,
            "y2": 1558,
            "text": "Staatsangehörigkeit:",
            "text_entropy": 0.141357421875
          },
          {
            "id": 3,
            "x1": 140,
            "y1": 1975,
            "x2": 310,
            "y2": 2014,
            "text": "Aktuelle",
            "text_entropy": 0.11651611328125
          },
          {
            "id": 4,
            "x1": 317,
            "y1": 1974,
            "x2": 625,
            "y2": 2019,
            "text": "Jahresbeiträge:",
            "text_entropy": 0.0947265625
          },
          {
            "id": 5,
            "x1": 138,
            "y1": 1081,
            "x2": 440,
            "y2": 1119,
            "text": "Geburtsdatum:",
            "text_entropy": 0.138671875
          },
          {
            "id": 6,
            "x1": 132,
            "y1": 2039,
            "x2": 477,
            "y2": 2075,
            "text": "Familienmitgliedschaft",
            "text_entropy": 0.14794921875
          },
          {
            "id": 7,
            "x1": 483,
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            "x2": 534,
            "y2": 2074,
            "text": "gilt",
            "text_entropy": 0.07037353515625
          },
          {
            "id": 8,
            "x1": 536,
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            "x2": 586,
            "y2": 2074,
            "text": "für",
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          {
            "id": 9,
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            "text": "1-2",
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            "id": 11,
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            "text": "Kinder",
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            "text": "welche",
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            "id": 20,
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            "id": 22,
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            "y2": 2069,
            "text": "einem",
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          {
            "id": 23,
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            "id": 24,
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            "id": 25,
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            "y2": 1231,
            "text": "Straße,",
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            "y2": 1227,
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            "text": "Jahresende",
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            "id": 36,
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            "x2": 318,
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            "y2": 3195,
            "text": "selbigen,",
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            "id": 212,
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          {
            "id": 213,
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          {
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          {
            "id": 215,
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          {
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          },
          {
            "id": 218,
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          },
          {
            "id": 219,
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            "text": "notwendig,",
            "text_entropy": 0.10693359375
          },
          {
            "id": 220,
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          },
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          {
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            "x2": 2090,
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            "text": "90,--",
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          },
          {
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          {
            "id": 228,
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          {
            "id": 229,
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          },
          {
            "id": 231,
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            "text": "je-",
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          },
          {
            "id": 232,
            "x1": 2072,
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            "y2": 1654,
            "text": "u.ä.",
            "text_entropy": 0.01421356201171875
          },
          {
            "id": 233,
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          },
          {
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          },
          {
            "id": 235,
            "x1": 142,
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            "y2": 2433,
            "text": "Musterstadt,",
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          },
          {
            "id": 236,
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          {
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            "text": "Vereinsheim",
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          {
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          {
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            "text": "Mustermann",
            "text_entropy": 0.011993408203125
          },
          {
            "id": 246,
            "x1": 604,
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            "y2": 1124,
            "text": "13.06.1990",
            "text_entropy": 0.10137939453125
          },
          {
            "id": 247,
            "x1": 590,
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            "y2": 1337,
            "text": "33445",
            "text_entropy": 0.05731201171875
          },
          {
            "id": 248,
            "x1": 1324,
            "y1": 2322,
            "x2": 1420,
            "y2": 2407,
            "text": "M.",
            "text_entropy": 0.06866455078125
          },
          {
            "id": 249,
            "x1": 1443,
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            "text": "Mustermann",
            "text_entropy": 0.0271148681640625
          },
          {
            "id": 250,
            "x1": 616,
            "y1": 717,
            "x2": 1025,
            "y2": 803,
            "text": "01.01.2023",
            "text_entropy": 0.08642578125
          },
          {
            "id": 251,
            "x1": 690,
            "y1": 824,
            "x2": 1056,
            "y2": 905,
            "text": "Maximilian",
            "text_entropy": 0.10357666015625
          },
          {
            "id": 252,
            "x1": 586,
            "y1": 1494,
            "x2": 645,
            "y2": 1562,
            "text": "X",
            "text_entropy": 0.440185546875
          },
          {
            "id": 253,
            "x1": 935,
            "y1": 1250,
            "x2": 1281,
            "y2": 1340,
            "text": "Musterstadt",
            "text_entropy": 0.139404296875
          },
          {
            "id": 254,
            "x1": 718,
            "y1": 1504,
            "x2": 800,
            "y2": 1559,
            "text": "tsch",
            "text_entropy": 0.1427001953125
          },
          {
            "id": 255,
            "x1": 1718,
            "y1": 1066,
            "x2": 1814,
            "y2": 1131,
            "text": "Am",
            "text_entropy": 0.419921875
          },
          {
            "id": 256,
            "x1": 489,
            "y1": 2401,
            "x2": 492,
            "y2": 2445,
            "text": ",",
            "text_entropy": 0.302734375
          }
        ],
        "fulltext": "Aufnahmeantrag\n|\nfür Erwachsene u. Jugendliche ab 16\na\nincl. Sepamandat u. Datenschutzerklärung\nHiermit beantrage ich die Mitgliedschaft im Sportverein NatifSports.\n(Zudem beantrage ich als aktive/r Fußballspieler/in ebenfalls die Mitgliedschaft im FC 92 Natif, solange der Spielbetrieb dies\nerfordert.)\nn\n01.01.2023\nMaximilian\nMustermann\n13.06.1990\nZum Vereinsheim\n33445\n031 65432\nEintrittsdatum:\nVorname:\nName:\nAm\n[X.m\nGeburtsdatum:\nGeschlecht:\n17\nd\nW\nStraße, HsNr.:\nMusterstadt\nPLZ, Ort:\n749. 151 687899\nFestnetz:\nMobil:\nStaatsangehörigkeit: X\ntsch\n(andere)\nDeutsch\nGymnastik / Aerobic / Turnen u.ä.\nLAktives Mitglied in der Sparte\nFußball\nBoxen\nals Fördermitglied mit\nvollem Beitrag\n% Beitrag\nFamilienmitgliedschaft über folgenden Hauptzahler:\nAktuelle Jahresbeiträge:\nFamilienmitgliedschaft gilt für 1-2 Erwachsene incl. deren Kinder bis einschließlich dem 18. Lebensjahr, welche alle in einem Haushalt leben.\nErwachsene 50,-- €\nKinder-u. Jugendliche 25,-- €\nFamilien 90,-- €\nIch habe Kenntnis von der Satzung genommen und erkenne diese an. Die Satzung liegt jederzeit im Sport-\nheim aus und ist im Internet unter natif.ai zu finden.\nMusterstadt, , 30.12.2022\nOrt, Datum\nM. Mustermann\nUnterschrift des neuen Mitglieds\nUnterschrift Erziehungsberechtige/r\nUnterschrift Erziehungsberechtige/r\nBei Minderjährigen sind generell die Unterschriften aller Erziehungsberechtigter erforderlich.\nMit der Unterschrift erkläre ich mich/wir uns bereit, die Beitragszahlung zu übernehmen. Diese Schuld-\nübernahme ist bis zur Volljährigkeit des Kindes begrenzt. Ich stimme der Speicherung, Verarbeitung und\nNutzung meiner personenbezogenen Daten (siehe Datenschutzerklärung) zu, soweit es für Vereins-/Ver-\nbandszwecke erforderlich ist.\nEin Vereinsaustritt hat immer mindestens einen Monat vor Jahresende schriftlich zu erfolgen und ist je-\nweils nur zum Jahresende gültig. Die Datenschutzerklärung ist zwingend notwendig, bei Verweigerung\nder selbigen, kann die Mitgliedschaft nicht erfolgen."
      }
    ]
  },
  "page_images": {
    "pages": [
      "/processing/results/bfb819fb-b193-42fa-ad19-8ad33aa8831b/page-images/1"
    ]
  },
  "hocr": "/processing/results/bfb819fb-b193-42fa-ad19-8ad33aa8831b/hocr",
  "language": {
    "iso_639_1": "de"
  },
  "thumbnail": "/processing/results/bfb819fb-b193-42fa-ad19-8ad33aa8831b/thumbnail"
}
Show more +
C#
Python
PHP
NodeJS
Java
using Newtonsoft.Json.Linq;

using (HttpClient httpClient = new HttpClient())
{
    string baseURL = "https://api.natif.ai";
    string workflow = "invoice_extraction";
    string apiKey = "<API_KEY>";    // TODO: Insert or load your API-key secret here
    string filePath = "<FILE_PATH>";    // TODO: Insert or load your file path here

    using (HttpRequestMessage request = new HttpRequestMessage(new HttpMethod("POST"), baseURL + "/processing/" + workflow + "?include=extractions"))
    {
        request.Headers.TryAddWithoutValidation("accept", "application/json");
        request.Headers.TryAddWithoutValidation("Authorization", "ApiKey " + apiKey);

        MultipartFormDataContent multipartContent = new MultipartFormDataContent();
        ByteArrayContent file1 = new ByteArrayContent(File.ReadAllBytes(filePath));
        multipartContent.Add(file1, "file", Path.GetFileName(filePath));
        multipartContent.Add(new StringContent("{\"language\": \"de\"}"), "parameters");
        request.Content = multipartContent;

        HttpResponseMessage response = await httpClient.SendAsync(request);

        string responseString = await response.Content.ReadAsStringAsync();
        JObject responseJson = JObject.Parse(responseString);
        if (responseJson["extractions"]["vendor"] != null
            && responseJson["extractions"]["vendor"]["name"] != null)
        {
            JToken vendorName = responseJson["extractions"]["vendor"]["name"];
            Console.WriteLine("Vendor name: " + vendorName["value"].ToString());
            Console.WriteLine("Vendor name confidence: " + vendorName["confidence"].ToString());
        }
        else
        {
            Console.WriteLine("Vendor name could not be extracted.");
        }
    }
}
Show more +
import json
import requests
import urllib.parse

base_url = "https://api.natif.ai"
workflow = "invoice_extraction"
api_key = "<API_KEY>"  # TODO: Insert or load your API-key secret here
file_path = "<FILE_PATH>"  # TODO: Insert or load your file path here

language = "de"


def process_via_natif_api(file_path, workflow, language, include="extractions"):
    # Encapsulates HTTP calls to the natif.ai processing API
    headers = {"Accept": "application/json", "Authorization": "ApiKey " + api_key}
    params = {"include": include}
    workflow_config = {"language": language}
    url = f"{base_url}/processing/{workflow}?{urllib.parse.urlencode(params)}"

    with open(file_path, "rb") as file:
        response = requests.post(
            url,
            headers=headers,
            data={"parameters": json.dumps(workflow_config)},
            files={"file": file},
        )
        if not response.ok:
            raise Exception(response.text)

        # ADVANCED: Retry logic for exceptionally long-running workflows
        while response.status_code == 202:
            processing_id = response.json()["processing_id"]
            RESULT_URI = f"${base_url}/processing/results/{processing_id}?{params}"
            url = RESULT_URI.format(
                processing_id=processing_id, params=urllib.parse.urlencode(params)
            )
            response = requests.get(url, headers=headers)

        return response.json()


if __name__ == "__main__":
    # Submit a file for receipt extraction
    result = process_via_natif_api(file_path, workflow, language, include="extractions")

    # Print one of the extracted values alongside its extraction confidence
    vendor = result.get("extractions").get("vendor").get("name")
    if vendor is not None:
        print(
            "Vendor name:",
            result.get("extractions")
            .get("vendor", {})
            .get("name", {})
            .get("value"),
        )
        print(
            "Vendor name confidence:",
            result.get("extractions")
            .get("vendor", {})
            .get("name", {})
            .get("confidence"),
        )
    else:
        print("Vendor name could not be extracted")
Show more +
<?php
$baseURL = "https://api.natif.ai";
$workflow = "invoice_extraction";
$apiKey = "<API_KEY>";   # TODO: Insert or load your API-key secret here
$filePath = "<FILE_PATH>";   # TODO: Insert or load your file path here

if (!file_exists($filePath)) {
    echo ("The file {$filePath} does not exist");
    return 1;
}

$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, "{$baseURL}/processing/{$workflow}?include=extractions");
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_CUSTOMREQUEST, "POST");
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Accept: application/json",
    "Authorization: ApiKey {$apiKey}",
    "Content-Type: multipart/form-data",
]);
curl_setopt($ch, CURLOPT_POSTFIELDS, [
    "file" => new CURLFile($filePath),
    "parameters" => '{"language": "de"}',
]);

$response = curl_exec($ch);
$httpcode = curl_getinfo($ch, CURLINFO_HTTP_CODE);
curl_close($ch);

if ($httpcode == 401) {
    echo ("Invalid credentials");
    return 1;
}

$json_data = json_decode($response, true);
$vendor_name = $json_data["extractions"]["vendor"]["name"] ?? false;
if ($vendor_name) {
    echo ("Vendor name: " . $vendor_name["value"] . "\n");
    echo ("Vendor name confidence: " . $vendor_name["confidence"]);
} else {
    echo ("Vendor name could not be extracted");
}
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package com.natif;

import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.io.OutputStream;
import java.net.HttpURLConnection;
import java.net.URL;
import java.net.URLConnection;
import java.nio.charset.StandardCharsets;
import java.util.ArrayList;
import java.util.UUID;
import com.google.gson.*;

public class InvoiceExtraction {
    private static final String baseURL = "https://api.natif.ai";
    private static final String workflow = "invoice_extraction";
    private static final String apiKey = "<API_KEY>"; // TODO: Insert or load your API-key secret here
    private static final String filePath = "<FILE_PATH>"; // TODO: Insert or load your file path here

    private static final ArrayList<String> params = new ArrayList<String>();
    static {
        params.add("include=extractions");
    }

    private static final String EOL = "\r\n";

    private static String natifApi() throws IOException {
        String responseString = "";
        try (FileInputStream file = new FileInputStream(filePath)) {
            String urlBase = baseURL + "/processing/%s?%s";
            HttpURLConnection con = (HttpURLConnection) new URL(String.format(urlBase, workflow, params))
                    .openConnection();
            final String boundary = UUID.randomUUID().toString();
            con.setDoOutput(true);
            con.setRequestMethod("POST");
            con.setRequestProperty("Content-Type", "multipart/form-data; boundary=" + boundary);
            con.setRequestProperty("Accept", "application/json");
            con.setRequestProperty("Authorization", "ApiKey " + apiKey);
            try (OutputStream out = con.getOutputStream()) {
                out.write(("--" + boundary + EOL +
                        "Content-Disposition: form-data; name=\"file\"; " +
                        "filename=\"" + filePath + "\"" + EOL +
                        "Content-Type: " + URLConnection.guessContentTypeFromName(filePath) + EOL + EOL)
                        .getBytes(StandardCharsets.UTF_8));
                byte[] buffer = new byte[128];
                int size = -1;
                while (-1 != (size = file.read(buffer))) {
                    out.write(buffer, 0, size);
                }
                out.write((EOL + "--" + boundary + EOL +
                        "Content-Disposition: form-data; name=\"parameters\" " + EOL + EOL +
                        "{\"language\": \"de\"}")
                        .getBytes(StandardCharsets.UTF_8));
                out.write((EOL + "--" + boundary + "--" + EOL).getBytes(StandardCharsets.UTF_8));
                out.flush();
                InputStream inputStream = con.getInputStream();
                BufferedReader bufferedReader = new BufferedReader(
                        new InputStreamReader(inputStream));
                StringBuilder response = new StringBuilder();
                String currentLine;

                while ((currentLine = bufferedReader.readLine()) != null)
                    response.append(currentLine);
                responseString = response.toString();
                bufferedReader.close();
            } finally {
                con.disconnect();
            }
            return responseString;
        }
    }

    public static void main(String[] args) throws IOException {
        String responseString = natifApi();
        Gson gson = new Gson();
        JsonObject responseJson = gson.fromJson(responseString, JsonObject.class);
        // Enter your code here
        JsonObject extractions = responseJson.getAsJsonObject("extractions");
        JsonObject vendor = extractions.getAsJsonObject("vendor");
        if (!vendor.isJsonNull()) {
            String name = vendor.getAsJsonObject("name").get("value").getAsString();
            System.out.printf("Vendor name: %s\n", name);
            String confidence = vendor.getAsJsonObject("name").get("confidence").getAsString();
            System.out.printf("Vendor name confidence: %s\n", confidence);
        } else {
            System.out.println("Vendor name could not be extracted.");
        }

    }
}
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