AI classification
for your software

What we do

We have developed a workflow that performs the individual process steps automatically. This workflow combines our Deep OCR, document classification and extraction into a single API call – simply and efficiently. Thanks to its Deep OCR, natif.ai classification technology can classify documents into more than 1000 classes and different business processes.
The software delivers real-time results, reduces manual effort, requires no setup costs and produces immediate savings. Plus, the entire process is super easy and quick to integrate.

Individual classification

With our technology, you can define your own document classes. Training the AI ​​also works with just a few examples.

Accuracy

Our AI models have been trained with hundreds of thousands of documents and extract all important information with high precision.

Speed

Thanks to high-performance GPUs, our AI processes documents in real time.

Active learning

Automated processes are constantly improving the recognition rates of our technology.

Plug & play

Thanks to Rest API, our AI models are quickly integrated into existing systems.

Robust reading

Our Deep OCR reads even low-quality documents and can be specially adapted to difficult use cases.

Data protection

We are 100 % GDPR- and Schrems II-compliant. We process the data on our servers and dispense with service providers.

AI Boost

Our AI models directly enable your software to automate documents.

Document type

Delivery note

Receiver name

Alfred Schneider

Receiver address

Muttweg 3

Date

01.05.2022

Delivery No.

3931

Article No. (1)

2912-282

Description (1)

Hook-M/3

Vendor

Triskona GmbH

Vendor VAT ID

DE 4567883213

{
  "processing_id": "e0e053a8-9efe-4a40-a5b3-758b69da39bb",
  "available_results": [
    "extractions",
    "classifications",
    "pdf",
    "ocr",
    "page-images",
    "hocr",
    "language",
    "thumbnail"
  ],
  "extractions": {
    "schema_version": 2,
    "document_type": "delivery note",
    "customer": {
      "name": {
        "validation_problem": false,
        "note": "",
        "confidence": 0.99985,
        "bbox_refs": [
          {
            "page_num": 1,
            "bbox_id": 3
          },
          {
            "page_num": 1,
            "bbox_id": 21
          }
        ],
        "value": "Alfred Schneider"
      },
      "address": {
        "validation_problem": false,
        "note": "",
        "confidence": 0.9998,
        "bbox_refs": [
          {
            "page_num": 1,
            "bbox_id": 10
          },
          {
            "page_num": 1,
            "bbox_id": 11
          },
          {
            "page_num": 1,
            "bbox_id": 1
          },
          {
            "page_num": 1,
            "bbox_id": 2
          }
        ],
        "value": "Mutweg 3 66117 Saarbrücken"
      },
...
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Document type

Rejection legal expenses insurance

Receiver name

Rechtsanwaltskanzlei Müller

Receiver address

Petersstraße 1

Receiver ZIP

49808

Receiver city

Lingen

Date

24.03.2021

Sender name

Saar Direct Versicherung

Sender address

Postfach 21 09 07

Subject

 Deckungsanfrage

{
  "processing_id": "220a05b5-a313-46dc-9b53-7db32a15eced",
  "available_results": [
    "extractions",
    "pdf",
    "ocr",
    "page-images",
    "hocr",
    "language",
    "thumbnail"
  ],
  "extractions": {
    "schema_version": 1,
    "document_type": "letter",
    "receiver": {
      "name": {
        "validation_problem": false,
        "note": "",
        "confidence": 0.9998,
        "bbox_refs": [
          {
            "page_num": 1,
            "bbox_id": 92
          },
          {
            "page_num": 1,
            "bbox_id": 93
          }
        ],
        "value": "Rechtsanwaltskanzlei Müller"
      },
      "address": {
        "address_line_1": {
          "validation_problem": false,
          "note": "",
          "confidence": 0.99985,
          "bbox_refs": [
            {
              "page_num": 1,
              "bbox_id": 94
            },
            {
              "page_num": 1,
              "bbox_id": 95
            }
          ],
          "value": "Petersstraße 1"
        },
....
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Document type

Invoice

Receiver address

Erfurterstrasse 13

Sender name

JOKO Service

Sender address

Lebacher Sand 11

Invoice No.

M1675

Invoice date

13.03.2019

Article No. (1)

B-3025-078

Price total (1)

120,00

Tax No.

91/200/53688

{
  "schema_version": 1,
  "document_type": "invoice",
  "customer": {
    "name": {
      "validation_problem": false,
      "note": "",
      "confidence": 0.99985,
      "bbox_refs": [
        {
          "page_num": 1,
          "bbox_id": 34
        },
        {
          "page_num": 1,
          "bbox_id": 35
        }
      ],
      "value": "Klaus Gotti"
    },
    "address": {
      "validation_problem": false,
      "note": "",
      "confidence": 0.999925,
      "bbox_refs": [
        {
          "page_num": 1,
          "bbox_id": 36
        },
        {
          "page_num": 1,
          "bbox_id": 37
        },
        {
          "page_num": 1,
          "bbox_id": 30
        },
        {
          "page_num": 1,
          "bbox_id": 31
        }
      ],
      "value": "Erforterstrasse 13 66111 Saarbrücken"
    },
....
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How we do it

Our models have been trained to enable enterprise software to classify large volumes of data in the shortest possible time. The classifier has been trained on millions of documents. As a result, it can classify documents into more than 1000 classes as well as various business transactions. Our customers, such as large DMS providers and insurance companies, rely on our technology every day. The classification is ready to use without any setup. For special requirements, the AI can be easily customized.
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.");
        }
    }
}
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Rest API

Can be integrated into existing processes in just a few minutes, thanks to support for common programming languages such as C#, PHP, Python, Java or NodeJS. Our documentation easily guides you through the integration processes. We support both synchronous and asynchronous data transfer. 
In the first step, documents can be uploaded via the API. Our software supports a whole range of file formats. These are currently the image formats JPEG, PNG, BMMP, GIF, TIFF and the document format PDF. 

Einfach Integration dank Make-Plugin

Easy integration thanks to Make-Plugin

Intuitive use of our technology and easy integration into existing processes such as in the DocuWare context thanks to our Make plugin.

Data extraction

We provide the key information as a structured JSON format via the API. For each data point, it also specifies the exact position on the document, the value and the confidence level. In addition to the JSON file, we provide a PDF/A file with the text level.
{
  "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,
            "y1": 2040,
            "x2": 534,
            "y2": 2074,
            "text": "gilt",
            "text_entropy": 0.07037353515625
          },
          {
            "id": 8,
            "x1": 536,
            "y1": 2040,
            "x2": 586,
            "y2": 2074,
            "text": "für",
            "text_entropy": 0.06671142578125
          },
          {
            "id": 9,
            "x1": 588,
            "y1": 2040,
            "x2": 639,
            "y2": 2070,
            "text": "1-2",
            "text_entropy": 0.07904052734375
          },
          {
            "id": 10,
            "x1": 645,
            "y1": 2039,
            "x2": 820,
            "y2": 2071,
            "text": "Erwachsene",
            "text_entropy": 0.1488037109375
          },
          {
            "id": 11,
            "x1": 822,
            "y1": 2039,
            "x2": 891,
            "y2": 2071,
            "text": "incl.",
            "text_entropy": 0.1458740234375
          },
          {
            "id": 12,
            "x1": 893,
            "y1": 2039,
            "x2": 982,
            "y2": 2071,
            "text": "deren",
            "text_entropy": 0.06317138671875
          },
          {
            "id": 13,
            "x1": 984,
            "y1": 2040,
            "x2": 1081,
            "y2": 2071,
            "text": "Kinder",
            "text_entropy": 0.0614013671875
          },
          {
            "id": 14,
            "x1": 1087,
            "y1": 2040,
            "x2": 1132,
            "y2": 2070,
            "text": "bis",
            "text_entropy": 0.0265045166015625
          },
          {
            "id": 15,
            "x1": 1134,
            "y1": 2040,
            "x2": 1334,
            "y2": 2075,
            "text": "einschließlich",
            "text_entropy": 0.1434326171875
          },
          {
            "id": 16,
            "x1": 1336,
            "y1": 2039,
            "x2": 1406,
            "y2": 2069,
            "text": "dem",
            "text_entropy": 0.108642578125
          },
          {
            "id": 17,
            "x1": 1412,
            "y1": 2039,
            "x2": 1458,
            "y2": 2069,
            "text": "18.",
            "text_entropy": 0.05975341796875
          },
          {
            "id": 18,
            "x1": 1465,
            "y1": 2039,
            "x2": 1635,
            "y2": 2075,
            "text": "Lebensjahr,",
            "text_entropy": 0.11431884765625
          },
          {
            "id": 19,
            "x1": 1640,
            "y1": 2038,
            "x2": 1744,
            "y2": 2069,
            "text": "welche",
            "text_entropy": 0.12548828125
          },
          {
            "id": 20,
            "x1": 1750,
            "y1": 2038,
            "x2": 1801,
            "y2": 2068,
            "text": "alle",
            "text_entropy": 0.01308441162109375
          },
          {
            "id": 21,
            "x1": 1803,
            "y1": 2038,
            "x2": 1840,
            "y2": 2069,
            "text": "in",
            "text_entropy": 0.1436767578125
          },
          {
            "id": 22,
            "x1": 1842,
            "y1": 2038,
            "x2": 1939,
            "y2": 2069,
            "text": "einem",
            "text_entropy": 0.04168701171875
          },
          {
            "id": 23,
            "x1": 1945,
            "y1": 2038,
            "x2": 2074,
            "y2": 2069,
            "text": "Haushalt",
            "text_entropy": 0.100341796875
          },
          {
            "id": 24,
            "x1": 2076,
            "y1": 2038,
            "x2": 2173,
            "y2": 2069,
            "text": "leben.",
            "text_entropy": 0.0246734619140625
          },
          {
            "id": 25,
            "x1": 132,
            "y1": 1187,
            "x2": 289,
            "y2": 1231,
            "text": "Straße,",
            "text_entropy": 0.07049560546875
          },
          {
            "id": 26,
            "x1": 291,
            "y1": 1190,
            "x2": 420,
            "y2": 1227,
            "text": "HsNr.:",
            "text_entropy": 0.13427734375
          },
          {
            "id": 27,
            "x1": 140,
            "y1": 3093,
            "x2": 248,
            "y2": 3130,
            "text": "weils",
            "text_entropy": 0.036041259765625
          },
          {
            "id": 28,
            "x1": 254,
            "y1": 3101,
            "x2": 330,
            "y2": 3130,
            "text": "nur",
            "text_entropy": 0.054779052734375
          },
          {
            "id": 29,
            "x1": 332,
            "y1": 3100,
            "x2": 416,
            "y2": 3130,
            "text": "zum",
            "text_entropy": 0.06951904296875
          },
          {
            "id": 30,
            "x1": 424,
            "y1": 3092,
            "x2": 660,
            "y2": 3130,
            "text": "Jahresende",
            "text_entropy": 0.05487060546875
          },
          {
            "id": 31,
            "x1": 662,
            "y1": 3094,
            "x2": 791,
            "y2": 3137,
            "text": "gültig.",
            "text_entropy": 0.12481689453125
          },
          {
            "id": 32,
            "x1": 793,
            "y1": 3094,
            "x2": 868,
            "y2": 3129,
            "text": "Die",
            "text_entropy": 0.06549072265625
          },
          {
            "id": 33,
            "x1": 870,
            "y1": 3093,
            "x2": 1312,
            "y2": 3138,
            "text": "Datenschutzerklärung",
            "text_entropy": 0.145751953125
          },
          {
            "id": 34,
            "x1": 1314,
            "y1": 3094,
            "x2": 1374,
            "y2": 3138,
            "text": "ist",
            "text_entropy": 0.05859375
          },
          {
            "id": 35,
            "x1": 1376,
            "y1": 3094,
            "x2": 1569,
            "y2": 3138,
            "text": "zwingend",
            "text_entropy": 0.0672607421875
          },
          {
            "id": 36,
            "x1": 139,
            "y1": 620,
            "x2": 318,
            "y2": 658,
            "text": "erfordert.)",
            "text_entropy": 0.08984375
          },
          {
            "id": 37,
            "x1": 133,
            "y1": 3152,
            "x2": 216,
            "y2": 3189,
            "text": "der",
            "text_entropy": 0.10498046875
          },
          {
            "id": 38,
            "x1": 218,
            "y1": 3152,
            "x2": 400,
            "y2": 3195,
            "text": "selbigen,",
            "text_entropy": 0.08026123046875
          },
          {
            "id": 39,
            "x1": 402,
            "y1": 3152,
            "x2": 507,
            "y2": 3188,
            "text": "kann",
            "text_entropy": 0.0704345703125
          },
          {
            "id": 40,
            "x1": 509,
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            "x2": 578,
            "y2": 3188,
            "text": "die",
            "text_entropy": 0.06195068359375
          },
          {
            "id": 41,
            "x1": 584,
            "y1": 3152,
            "x2": 867,
            "y2": 3196,
            "text": "Mitgliedschaft",
            "text_entropy": 0.147216796875
          },
          {
            "id": 42,
            "x1": 869,
            "y1": 3151,
            "x2": 977,
            "y2": 3191,
            "text": "nicht",
            "text_entropy": 0.036041259765625
          },
          {
            "id": 43,
            "x1": 984,
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            "x2": 1159,
            "y2": 3196,
            "text": "erfolgen.",
            "text_entropy": 0.025146484375
          },
          {
            "id": 44,
            "x1": 139,
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            "x2": 244,
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            "text": "heim",
            "text_entropy": 0.07635498046875
          },
          {
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            "x2": 326,
            "y2": 2236,
            "text": "aus",
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          },
          {
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            "y2": 2236,
            "text": "und",
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          },
          {
            "id": 47,
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            "text": "ist",
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          },
          {
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            "y2": 2235,
            "text": "im",
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          },
          {
            "id": 49,
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            "x2": 699,
            "y2": 2236,
            "text": "Internet",
            "text_entropy": 0.11053466796875
          },
          {
            "id": 50,
            "x1": 704,
            "y1": 2202,
            "x2": 815,
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            "text": "unter",
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          },
          {
            "id": 51,
            "x1": 822,
            "y1": 2200,
            "x2": 965,
            "y2": 2236,
            "text": "natif.ai",
            "text_entropy": 0.03289794921875
          },
          {
            "id": 52,
            "x1": 970,
            "y1": 2209,
            "x2": 1016,
            "y2": 2236,
            "text": "zu",
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          },
          {
            "id": 53,
            "x1": 1023,
            "y1": 2200,
            "x2": 1159,
            "y2": 2236,
            "text": "finden.",
            "text_entropy": 0.1424560546875
          },
          {
            "id": 54,
            "x1": 132,
            "y1": 2715,
            "x2": 211,
            "y2": 2753,
            "text": "Bei",
            "text_entropy": 0.1429443359375
          },
          {
            "id": 55,
            "x1": 226,
            "y1": 2713,
            "x2": 530,
            "y2": 2759,
            "text": "Minderjährigen",
            "text_entropy": 0.060394287109375
          },
          {
            "id": 56,
            "x1": 532,
            "y1": 2714,
            "x2": 625,
            "y2": 2758,
            "text": "sind",
            "text_entropy": 0.1168212890625
          },
          {
            "id": 57,
            "x1": 627,
            "y1": 2716,
            "x2": 797,
            "y2": 2759,
            "text": "generell",
            "text_entropy": 0.034698486328125
          },
          {
            "id": 58,
            "x1": 799,
            "y1": 2714,
            "x2": 869,
            "y2": 2756,
            "text": "die",
            "text_entropy": 0.14697265625
          },
          {
            "id": 59,
            "x1": 876,
            "y1": 2714,
            "x2": 1166,
            "y2": 2754,
            "text": "Unterschriften",
            "text_entropy": 0.09185791015625
          },
          {
            "id": 60,
            "x1": 1174,
            "y1": 2715,
            "x2": 1269,
            "y2": 2757,
            "text": "aller",
            "text_entropy": 0.08587646484375
          },
          {
            "id": 61,
            "x1": 1275,
            "y1": 2713,
            "x2": 1744,
            "y2": 2758,
            "text": "Erziehungsberechtigter",
            "text_entropy": 0.149169921875
          },
          {
            "id": 62,
            "x1": 1746,
            "y1": 2713,
            "x2": 1999,
            "y2": 2752,
            "text": "erforderlich.",
            "text_entropy": 0.1318359375
          },
          {
            "id": 63,
            "x1": 139,
            "y1": 2948,
            "x2": 412,
            "y2": 2987,
            "text": "bandszwecke",
            "text_entropy": 0.1474609375
          },
          {
            "id": 64,
            "x1": 414,
            "y1": 2949,
            "x2": 651,
            "y2": 2988,
            "text": "erforderlich",
            "text_entropy": 0.08721923828125
          },
          {
            "id": 65,
            "x1": 653,
            "y1": 2949,
            "x2": 718,
            "y2": 2987,
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        "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."
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