Precise Extraction of all Information
Use unstructured content automatically in your following systems! Our AI structures all the information in your documents and passes it on as a JSON file for downstream processes.
Precise Extraction of all Information
Use unstructured content automatically in your following systems! Our AI structures all the information in your documents and passes it on as a JSON file for downstream processes.
Extract Line Item Data with AI
With our extraction, you can automatically convert PDFs or images from your documents into a simple JSON format. The AI provides you with all relevant information, including line item data. Our AI Document Automation Platform offers you numerous pre-trained extraction models for e.g. ID cards, invoices and receipts.
Line ItemsOur AI extracts truly all content – including tax and position data.
Validity CheckInformation such as IBAN and BIC are checked for validity by our AI.
StructuringAll data is assigned the appropriate value and confidence level.
Receiver Address
Erfurterstrasse 13
Sender
JOKO Service
Sender Address
Lebacher Sand 11
Invoice No.
M1675
Invoice Date
13.03.2019
Article No.
B-3025-078
Total Article “B-3025-…
120,00
Total Invoice
209,03
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"
....
Extract Line Item Data with AI
With our extraction, you can automatically convert PDFs or images from your documents into a simple JSON format. The AI provides you with all relevant information, including line item data.
Our AI Document Automation Platform offers you numerous pre-trained extraction models for e.g. ID cards, invoices and receipts.
Our AI Document Automation Platform offers you numerous pre-trained extraction models for e.g. ID cards, invoices and receipts.
Line ItemsOur AI extracts truly all content – including tax and position data.
Validity CheckInformation such as IBAN and BIC are checked for validity by our AI.
StructuringAll data is assigned the appropriate value and confidence level.
Receiver Address
Erfurterstrasse 13
Sender
JOKO Service
Sender Address
Lebacher Sand 11
Invoice No.
M1675
Invoice Date
13.03.2019
Article No.
B-3025-078
Total Article “B-3025-…
120,00
Total Invoice
209,03
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"
....
Our Technology
Benefit from data extraction with artificial intelligence and process your documents in real time. With our technology, even position data can be precisely read and processed in the downstream system. Even errors are detected by our AI and displayed to you as a hint.
Understanding Line Data
Our technology also extracts all data at position level. For example, description, order quantity and price can be assigned to a specific item.
The different items are recognized and assigned separately.
The different items are recognized and assigned separately.

Check Data Fields
Extracting data intelligently also means checking its content. Our AI recognizes, for example, whether an IBAN or BIC complies with the standards or whether the total amount specified is really the sum of the individual amounts. Tax amounts are also recalculated.

Our Technology
Benefit from data extraction with artificial intelligence and process your documents in real time. With our technology, even position data can be precisely read and processed in the downstream system. Even errors are detected by our AI and displayed to you as a hint.
Understanding Line Data
Our technology also extracts all data at position level. For example, description, order quantity and price can be assigned to a specific item.
The different items are recognized and assigned separately.
The different items are recognized and assigned separately.

Check Data Fields
Extracting data intelligently also means checking its content. Our AI recognizes, for example, whether an IBAN or BIC complies with the standards or whether the total amount specified is really the sum of the individual amounts. Tax amounts are also recalculated.

Structured Extraction
Our platform provides you with all the information of your documents as a structured JSON format via our API. For each data point it also includes the exact position on the document, the value and the confidence level. In addition to the JSON file, you will receive a PDF/A file with the text level.
Structured Extraction
Our platform provides you with all the information of your documents as a structured JSON format via our API. For each data point it also includes the exact position on the document, the value and the confidence level. In addition to the JSON file, you will receive 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,
"y1": 3151,
"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,
"y1": 3151,
"x2": 1159,
"y2": 3196,
"text": "erfolgen.",
"text_entropy": 0.025146484375
},
{
"id": 44,
"x1": 139,
"y1": 2198,
"x2": 244,
"y2": 2236,
"text": "heim",
"text_entropy": 0.07635498046875
},
{
"id": 45,
"x1": 249,
"y1": 2202,
"x2": 326,
"y2": 2236,
"text": "aus",
"text_entropy": 0.0650634765625
},
{
"id": 46,
"x1": 328,
"y1": 2198,
"x2": 411,
"y2": 2236,
"text": "und",
"text_entropy": 0.1259765625
},
{
"id": 47,
"x1": 413,
"y1": 2199,
"x2": 465,
"y2": 2233,
"text": "ist",
"text_entropy": 0.076171875
},
{
"id": 48,
"x1": 471,
"y1": 2199,
"x2": 528,
"y2": 2235,
"text": "im",
"text_entropy": 0.09423828125
},
{
"id": 49,
"x1": 530,
"y1": 2199,
"x2": 699,
"y2": 2236,
"text": "Internet",
"text_entropy": 0.11053466796875
},
{
"id": 50,
"x1": 704,
"y1": 2202,
"x2": 815,
"y2": 2236,
"text": "unter",
"text_entropy": 0.040252685546875
},
{
"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",
"text_entropy": 0.0556640625
},
{
"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,
"text": "ist.",
"text_entropy": 0.0955810546875
},
{
"id": 66,
"x1": 133,
"y1": 566,
"x2": 273,
"y2": 606,
"text": "(Zudem",
"text_entropy": 0.1494140625
},
{
"id": 67,
"x1": 280,
"y1": 567,
"x2": 447,
"y2": 606,
"text": "beantrage",
"text_entropy": 0.018829345703125
},
{
"id": 68,
"x1": 449,
"y1": 566,
"x2": 503,
"y2": 604,
"text": "ich",
"text_entropy": 0.062286376953125
},
{
"id": 69,
"x1": 505,
"y1": 568,
"x2": 559,
"y2": 599,
"text": "als",
"text_entropy": 0.00623321533203125
},
{
"id": 70,
"x1": 561,
"y1": 567,
"x2": 693,
"y2": 604,
"text": "aktive/r",
"text_entropy": 0.1490478515625
},
{
"id": 71,
"x1": 700,
"y1": 567,
"x2": 973,
"y2": 607,
"text": "Fußballspieler/in",
"text_entropy": 0.146240234375
},
{
"id": 72,
"x1": 980,
"y1": 568,
"x2": 1133,
"y2": 599,
"text": "ebenfalls",
"text_entropy": 0.068115234375
},
{
"id": 73,
"x1": 1135,
"y1": 571,
"x2": 1190,
"y2": 600,
"text": "die",
"text_entropy": 0.11004638671875
},
{
"id": 74,
"x1": 1196,
"y1": 570,
"x2": 1429,
"y2": 608,
"text": "Mitgliedschaft",
"text_entropy": 0.1361083984375
},
{
"id": 75,
"x1": 1431,
"y1": 570,
"x2": 1482,
"y2": 606,
"text": "im",
"text_entropy": 0.08831787109375
},
{
"id": 76,
"x1": 1484,
"y1": 571,
"x2": 1532,
"y2": 600,
"text": "FC",
"text_entropy": 0.037200927734375
},
{
"id": 77,
"x1": 1534,
"y1": 571,
"x2": 1582,
"y2": 600,
"text": "92",
"text_entropy": 0.03741455078125
},
{
"id": 78,
"x1": 1589,
"y1": 568,
"x2": 1679,
"y2": 604,
"text": "Natif,",
"text_entropy": 0.125244140625
},
{
"id": 79,
"x1": 1681,
"y1": 568,
"x2": 1813,
"y2": 606,
"text": "solange",
"text_entropy": 0.1226806640625
},
{
"id": 80,
"x1": 1820,
"y1": 569,
"x2": 1876,
"y2": 600,
"text": "der",
"text_entropy": 0.1483154296875
},
{
"id": 81,
"x1": 1883,
"y1": 568,
"x2": 2085,
"y2": 606,
"text": "Spielbetrieb",
"text_entropy": 0.09942626953125
},
{
"id": 82,
"x1": 2087,
"y1": 568,
"x2": 2153,
"y2": 599,
"text": "dies",
"text_entropy": 0.1346435546875
},
{
"id": 83,
"x1": 138,
"y1": 2437,
"x2": 210,
"y2": 2472,
"text": "Ort,",
"text_entropy": 0.11279296875
},
{
"id": 84,
"x1": 216,
"y1": 2436,
"x2": 327,
"y2": 2468,
"text": "Datum",
"text_entropy": 0.080810546875
},
{
"id": 85,
"x1": 133,
"y1": 507,
"x2": 301,
"y2": 546,
"text": "Hiermit",
"text_entropy": 0.1348876953125
},
{
"id": 86,
"x1": 309,
"y1": 509,
"x2": 509,
"y2": 552,
"text": "beantrage",
"text_entropy": 0.0843505859375
},
{
"id": 87,
"x1": 517,
"y1": 508,
"x2": 581,
"y2": 545,
"text": "ich",
"text_entropy": 0.0258636474609375
},
{
"id": 88,
"x1": 589,
"y1": 509,
"x2": 653,
"y2": 546,
"text": "die",
"text_entropy": 0.14599609375
},
{
"id": 89,
"x1": 669,
"y1": 508,
"x2": 951,
"y2": 553,
"text": "Mitgliedschaft",
"text_entropy": 0.1300048828125
},
{
"id": 90,
"x1": 953,
"y1": 510,
"x2": 1012,
"y2": 554,
"text": "im",
"text_entropy": 0.055450439453125
},
{
"id": 91,
"x1": 1020,
"y1": 510,
"x2": 1260,
"y2": 555,
"text": "Sportverein",
"text_entropy": 0.11822509765625
},
{
"id": 92,
"x1": 1269,
"y1": 510,
"x2": 1508,
"y2": 555,
"text": "NatifSports.",
"text_entropy": 0.149169921875
},
{
"id": 93,
"x1": 139,
"y1": 3034,
"x2": 211,
"y2": 3069,
"text": "Ein",
"text_entropy": 0.1407470703125
},
{
"id": 94,
"x1": 217,
"y1": 3033,
"x2": 510,
"y2": 3070,
"text": "Vereinsaustritt",
"text_entropy": 0.08441162109375
},
{
"id": 95,
"x1": 516,
"y1": 3033,
"x2": 582,
"y2": 3069,
"text": "hat",
"text_entropy": 0.062469482421875
},
{
"id": 96,
"x1": 588,
"y1": 3033,
"x2": 725,
"y2": 3070,
"text": "immer",
"text_entropy": 0.029205322265625
},
{
"id": 97,
"x1": 737,
"y1": 3033,
"x2": 964,
"y2": 3070,
"text": "mindestens",
"text_entropy": 0.0299530029296875
},
{
"id": 98,
"x1": 966,
"y1": 3035,
"x2": 1082,
"y2": 3071,
"text": "einen",
"text_entropy": 0.12548828125
},
{
"id": 99,
"x1": 1095,
"y1": 3035,
"x2": 1223,
"y2": 3070,
"text": "Monat",
"text_entropy": 0.01702880859375
},
{
"id": 100,
"x1": 1225,
"y1": 3042,
"x2": 1295,
"y2": 3070,
"text": "vor",
"text_entropy": 0.05462646484375
},
{
"id": 101,
"x1": 1297,
"y1": 3034,
"x2": 1531,
"y2": 3070,
"text": "Jahresende",
"text_entropy": 0.13818359375
},
{
"id": 102,
"x1": 1537,
"y1": 3034,
"x2": 1723,
"y2": 3070,
"text": "schriftlich",
"text_entropy": 0.1494140625
},
{
"id": 103,
"x1": 133,
"y1": 2604,
"x2": 343,
"y2": 2637,
"text": "Unterschrift",
"text_entropy": 0.09698486328125
},
{
"id": 104,
"x1": 350,
"y1": 2601,
"x2": 737,
"y2": 2642,
"text": "Erziehungsberechtige/r",
"text_entropy": 0.1478271484375
},
{
"id": 105,
"x1": 140,
"y1": 2775,
"x2": 220,
"y2": 2811,
"text": "Mit",
"text_entropy": 0.025665283203125
},
{
"id": 106,
"x1": 222,
"y1": 2774,
"x2": 295,
"y2": 2811,
"text": "der",
"text_entropy": 0.040863037109375
},
{
"id": 107,
"x1": 301,
"y1": 2774,
"x2": 542,
"y2": 2812,
"text": "Unterschrift",
"text_entropy": 0.1368408203125
},
{
"id": 108,
"x1": 544,
"y1": 2775,
"x2": 683,
"y2": 2811,
"text": "erkläre",
"text_entropy": 0.055694580078125
},
{
"id": 109,
"x1": 690,
"y1": 2774,
"x2": 757,
"y2": 2811,
"text": "ich",
"text_entropy": 0.0802001953125
},
{
"id": 110,
"x1": 762,
"y1": 2774,
"x2": 939,
"y2": 2817,
"text": "mich/wir",
"text_entropy": 0.127685546875
},
{
"id": 111,
"x1": 946,
"y1": 2783,
"x2": 1014,
"y2": 2811,
"text": "uns",
"text_entropy": 0.0022945404052734375
},
{
"id": 112,
"x1": 133,
"y1": 2831,
"x2": 371,
"y2": 2870,
"text": "übernahme",
"text_entropy": 0.133544921875
},
{
"id": 113,
"x1": 378,
"y1": 2833,
"x2": 432,
"y2": 2867,
"text": "ist",
"text_entropy": 0.1031494140625
},
{
"id": 114,
"x1": 439,
"y1": 2833,
"x2": 499,
"y2": 2870,
"text": "bis",
"text_entropy": 0.027862548828125
},
{
"id": 115,
"x1": 501,
"y1": 2839,
"x2": 569,
"y2": 2870,
"text": "zur",
"text_entropy": 0.1495361328125
},
{
"id": 116,
"x1": 576,
"y1": 2833,
"x2": 838,
"y2": 2875,
"text": "Volljährigkeit",
"text_entropy": 0.114990234375
},
{
"id": 117,
"x1": 846,
"y1": 2832,
"x2": 915,
"y2": 2870,
"text": "des",
"text_entropy": 0.041748046875
},
{
"id": 118,
"x1": 922,
"y1": 2832,
"x2": 1053,
"y2": 2869,
"text": "Kindes",
"text_entropy": 0.129150390625
},
{
"id": 119,
"x1": 1059,
"y1": 2833,
"x2": 1251,
"y2": 2876,
"text": "begrenzt.",
"text_entropy": 0.12176513671875
},
{
"id": 120,
"x1": 1253,
"y1": 2833,
"x2": 1320,
"y2": 2870,
"text": "Ich",
"text_entropy": 0.1075439453125
},
{
"id": 121,
"x1": 1322,
"y1": 2833,
"x2": 1481,
"y2": 2870,
"text": "stimme",
"text_entropy": 0.06549072265625
},
{
"id": 122,
"x1": 1483,
"y1": 2833,
"x2": 1558,
"y2": 2871,
"text": "der",
"text_entropy": 0.039154052734375
},
{
"id": 123,
"x1": 1560,
"y1": 2831,
"x2": 1820,
"y2": 2876,
"text": "Speicherung,",
"text_entropy": 0.12939453125
},
{
"id": 124,
"x1": 1827,
"y1": 2831,
"x2": 2087,
"y2": 2876,
"text": "Verarbeitung",
"text_entropy": 0.137451171875
},
{
"id": 125,
"x1": 2089,
"y1": 2833,
"x2": 2164,
"y2": 2870,
"text": "und",
"text_entropy": 0.11541748046875
},
{
"id": 126,
"x1": 133,
"y1": 2142,
"x2": 205,
"y2": 2179,
"text": "Ich",
"text_entropy": 0.0194091796875
},
{
"id": 127,
"x1": 211,
"y1": 2142,
"x2": 313,
"y2": 2179,
"text": "habe",
"text_entropy": 0.0877685546875
},
{
"id": 128,
"x1": 319,
"y1": 2142,
"x2": 497,
"y2": 2180,
"text": "Kenntnis",
"text_entropy": 0.03662109375
},
{
"id": 129,
"x1": 499,
"y1": 2151,
"x2": 577,
"y2": 2180,
"text": "von",
"text_entropy": 0.06622314453125
},
{
"id": 130,
"x1": 584,
"y1": 2143,
"x2": 655,
"y2": 2179,
"text": "der",
"text_entropy": 0.03411865234375
},
{
"id": 131,
"x1": 657,
"y1": 2143,
"x2": 819,
"y2": 2185,
"text": "Satzung",
"text_entropy": 0.06781005859375
},
{
"id": 132,
"x1": 821,
"y1": 2147,
"x2": 1045,
"y2": 2187,
"text": "genommen",
"text_entropy": 0.04522705078125
},
{
"id": 133,
"x1": 139,
"y1": 871,
"x2": 338,
"y2": 906,
"text": "Vorname:",
"text_entropy": 0.1453857421875
},
{
"id": 134,
"x1": 139,
"y1": 2893,
"x2": 312,
"y2": 2935,
"text": "Nutzung",
"text_entropy": 0.0689697265625
},
{
"id": 135,
"x1": 325,
"y1": 2893,
"x2": 462,
"y2": 2929,
"text": "meiner",
"text_entropy": 0.1488037109375
},
{
"id": 136,
"x1": 468,
"y1": 2892,
"x2": 871,
"y2": 2934,
"text": "personenbezogenen",
"text_entropy": 0.14208984375
},
{
"id": 137,
"x1": 877,
"y1": 2894,
"x2": 994,
"y2": 2929,
"text": "Daten",
"text_entropy": 0.0999755859375
},
{
"id": 138,
"x1": 139,
"y1": 978,
"x2": 276,
"y2": 1013,
"text": "Name:",
"text_entropy": 0.03277587890625
},
{
"id": 139,
"x1": 138,
"y1": 1404,
"x2": 326,
"y2": 1440,
"text": "Festnetz:",
"text_entropy": 0.1475830078125
},
{
"id": 140,
"x1": 139,
"y1": 762,
"x2": 441,
"y2": 798,
"text": "Eintrittsdatum:",
"text_entropy": 0.041748046875
},
{
"id": 141,
"x1": 143,
"y1": 1299,
"x2": 230,
"y2": 1338,
"text": "PLZ,",
"text_entropy": 0.0280609130859375
},
{
"id": 142,
"x1": 235,
"y1": 1299,
"x2": 306,
"y2": 1333,
"text": "Ort:",
"text_entropy": 0.1483154296875
},
{
"id": 143,
"x1": 202,
"y1": 1797,
"x2": 661,
"y2": 1846,
"text": "Familienmitgliedschaft",
"text_entropy": 0.1324462890625
},
{
"id": 144,
"x1": 669,
"y1": 1802,
"x2": 759,
"y2": 1839,
"text": "über",
"text_entropy": 0.1495361328125
},
{
"id": 145,
"x1": 761,
"y1": 1799,
"x2": 969,
"y2": 1844,
"text": "folgenden",
"text_entropy": 0.034149169921875
},
{
"id": 146,
"x1": 976,
"y1": 1801,
"x2": 1230,
"y2": 1846,
"text": "Hauptzahler:",
"text_entropy": 0.1490478515625
},
{
"id": 147,
"x1": 201,
"y1": 1711,
"x2": 271,
"y2": 1749,
"text": "als",
"text_entropy": 0.07305908203125
},
{
"id": 148,
"x1": 273,
"y1": 1712,
"x2": 570,
"y2": 1758,
"text": "Fördermitglied",
"text_entropy": 0.12939453125
},
{
"id": 149,
"x1": 577,
"y1": 1713,
"x2": 646,
"y2": 1749,
"text": "mit",
"text_entropy": 0.1461181640625
},
{
"id": 150,
"x1": 194,
"y1": 1618,
"x2": 359,
"y2": 1656,
"text": "LAktives",
"text_entropy": 0.056854248046875
},
{
"id": 151,
"x1": 366,
"y1": 1618,
"x2": 529,
"y2": 1663,
"text": "Mitglied",
"text_entropy": 0.0936279296875
},
{
"id": 152,
"x1": 531,
"y1": 1620,
"x2": 577,
"y2": 1663,
"text": "in",
"text_entropy": 0.047515869140625
},
{
"id": 153,
"x1": 585,
"y1": 1619,
"x2": 655,
"y2": 1656,
"text": "der",
"text_entropy": 0.01000213623046875
},
{
"id": 154,
"x1": 657,
"y1": 1619,
"x2": 789,
"y2": 1663,
"text": "Sparte",
"text_entropy": 0.0167388916015625
},
{
"id": 155,
"x1": 631,
"y1": 1510,
"x2": 800,
"y2": 1549,
"text": "Deutsch",
"text_entropy": 0.0960693359375
},
{
"id": 156,
"x1": 673,
"y1": 1976,
"x2": 923,
"y2": 2017,
"text": "Erwachsene",
"text_entropy": 0.0177459716796875
},
{
"id": 157,
"x1": 929,
"y1": 1978,
"x2": 1024,
"y2": 2021,
"text": "50,--",
"text_entropy": 0.1175537109375
},
{
"id": 158,
"x1": 1026,
"y1": 1979,
"x2": 1056,
"y2": 2016,
"text": "€",
"text_entropy": 0.14892578125
},
{
"id": 159,
"x1": 677,
"y1": 354,
"x2": 784,
"y2": 398,
"text": "incl.",
"text_entropy": 0.1341552734375
},
{
"id": 160,
"x1": 786,
"y1": 354,
"x2": 1090,
"y2": 406,
"text": "Sepamandat",
"text_entropy": 0.1402587890625
},
{
"id": 161,
"x1": 1092,
"y1": 365,
"x2": 1145,
"y2": 395,
"text": "u.",
"text_entropy": 0.0816650390625
},
{
"id": 162,
"x1": 1154,
"y1": 354,
"x2": 1672,
"y2": 404,
"text": "Datenschutzerklärung",
"text_entropy": 0.1182861328125
},
{
"id": 163,
"x1": 738,
"y1": 278,
"x2": 825,
"y2": 323,
"text": "für",
"text_entropy": 0.05645751953125
},
{
"id": 164,
"x1": 833,
"y1": 279,
"x2": 1118,
"y2": 324,
"text": "Erwachsene",
"text_entropy": 0.0716552734375
},
{
"id": 165,
"x1": 1120,
"y1": 281,
"x2": 1174,
"y2": 327,
"text": "u.",
"text_entropy": 0.06793212890625
},
{
"id": 166,
"x1": 1176,
"y1": 280,
"x2": 1458,
"y2": 330,
"text": "Jugendliche",
"text_entropy": 0.06793212890625
},
{
"id": 167,
"x1": 1466,
"y1": 282,
"x2": 1527,
"y2": 323,
"text": "ab",
"text_entropy": 0.038818359375
},
{
"id": 168,
"x1": 1535,
"y1": 281,
"x2": 1600,
"y2": 323,
"text": "16",
"text_entropy": 0.002410888671875
},
{
"id": 169,
"x1": 830,
"y1": 167,
"x2": 1518,
"y2": 250,
"text": "Aufnahmeantrag",
"text_entropy": 0.058349609375
},
{
"id": 170,
"x1": 943,
"y1": 1712,
"x2": 1077,
"y2": 1751,
"text": "vollem",
"text_entropy": 0.1473388671875
},
{
"id": 171,
"x1": 943,
"y1": 1618,
"x2": 1097,
"y2": 1656,
"text": "Fußball",
"text_entropy": 0.07550048828125
},
{
"id": 172,
"x1": 1004,
"y1": 2891,
"x2": 1127,
"y2": 2935,
"text": "(siehe",
"text_entropy": 0.054718017578125
},
{
"id": 173,
"x1": 1134,
"y1": 2890,
"x2": 1579,
"y2": 2935,
"text": "Datenschutzerklärung)",
"text_entropy": 0.1163330078125
},
{
"id": 174,
"x1": 1587,
"y1": 2900,
"x2": 1649,
"y2": 2932,
"text": "zu,",
"text_entropy": 0.037872314453125
},
{
"id": 175,
"x1": 1655,
"y1": 2891,
"x2": 1792,
"y2": 2928,
"text": "soweit",
"text_entropy": 0.053924560546875
},
{
"id": 176,
"x1": 1794,
"y1": 2895,
"x2": 1840,
"y2": 2926,
"text": "es",
"text_entropy": 0.0711669921875
},
{
"id": 177,
"x1": 1847,
"y1": 2890,
"x2": 1909,
"y2": 2925,
"text": "für",
"text_entropy": 0.114990234375
},
{
"id": 178,
"x1": 1916,
"y1": 2889,
"x2": 2184,
"y2": 2933,
"text": "Vereins-/Ver-",
"text_entropy": 0.10504150390625
},
{
"id": 179,
"x1": 1024,
"y1": 2775,
"x2": 1165,
"y2": 2817,
"text": "bereit,",
"text_entropy": 0.0887451171875
},
{
"id": 180,
"x1": 1167,
"y1": 2776,
"x2": 1233,
"y2": 2811,
"text": "die",
"text_entropy": 0.1484375
},
{
"id": 181,
"x1": 1235,
"y1": 2775,
"x2": 1550,
"y2": 2818,
"text": "Beitragszahlung",
"text_entropy": 0.078369140625
},
{
"id": 182,
"x1": 1556,
"y1": 2780,
"x2": 1608,
"y2": 2809,
"text": "zu",
"text_entropy": 0.061920166015625
},
{
"id": 183,
"x1": 1610,
"y1": 2772,
"x2": 1885,
"y2": 2810,
"text": "übernehmen.",
"text_entropy": 0.1427001953125
},
{
"id": 184,
"x1": 1887,
"y1": 2774,
"x2": 1999,
"y2": 2808,
"text": "Diese",
"text_entropy": 0.1448974609375
},
{
"id": 185,
"x1": 2006,
"y1": 2774,
"x2": 2153,
"y2": 2810,
"text": "Schuld-",
"text_entropy": 0.0643310546875
},
{
"id": 186,
"x1": 1055,
"y1": 2142,
"x2": 1138,
"y2": 2177,
"text": "und",
"text_entropy": 0.06591796875
},
{
"id": 187,
"x1": 1144,
"y1": 2140,
"x2": 1310,
"y2": 2177,
"text": "erkenne",
"text_entropy": 0.12744140625
},
{
"id": 188,
"x1": 1315,
"y1": 2141,
"x2": 1424,
"y2": 2177,
"text": "diese",
"text_entropy": 0.099365234375
},
{
"id": 189,
"x1": 1428,
"y1": 2150,
"x2": 1486,
"y2": 2177,
"text": "an.",
"text_entropy": 0.0205078125
},
{
"id": 190,
"x1": 1086,
"y1": 1714,
"x2": 1240,
"y2": 1757,
"text": "Beitrag",
"text_entropy": 0.03955078125
},
{
"id": 191,
"x1": 1159,
"y1": 1977,
"x2": 1352,
"y2": 2011,
"text": "Kinder-u.",
"text_entropy": 0.143798828125
},
{
"id": 192,
"x1": 1215,
"y1": 1083,
"x2": 1445,
"y2": 1119,
"text": "Geschlecht:",
"text_entropy": 0.1495361328125
},
{
"id": 193,
"x1": 1216,
"y1": 2603,
"x2": 1423,
"y2": 2636,
"text": "Unterschrift",
"text_entropy": 0.14404296875
},
{
"id": 194,
"x1": 1425,
"y1": 2602,
"x2": 1815,
"y2": 2640,
"text": "Erziehungsberechtige/r",
"text_entropy": 0.09716796875
},
{
"id": 195,
"x1": 1220,
"y1": 2435,
"x2": 1422,
"y2": 2468,
"text": "Unterschrift",
"text_entropy": 0.1142578125
},
{
"id": 196,
"x1": 1424,
"y1": 2436,
"x2": 1486,
"y2": 2467,
"text": "des",
"text_entropy": 0.11248779296875
},
{
"id": 197,
"x1": 1490,
"y1": 2442,
"x2": 1596,
"y2": 2467,
"text": "neuen",
"text_entropy": 0.078125
},
{
"id": 198,
"x1": 1607,
"y1": 2436,
"x2": 1753,
"y2": 2472,
"text": "Mitglieds",
"text_entropy": 0.149169921875
},
{
"id": 199,
"x1": 1256,
"y1": 1621,
"x2": 1384,
"y2": 1655,
"text": "Boxen",
"text_entropy": 0.128173828125
},
{
"id": 200,
"x1": 1308,
"y1": 1406,
"x2": 1436,
"y2": 1442,
"text": "Mobil:",
"text_entropy": 0.01202392578125
},
{
"id": 201,
"x1": 1354,
"y1": 1976,
"x2": 1593,
"y2": 2020,
"text": "Jugendliche",
"text_entropy": 0.0880126953125
},
{
"id": 202,
"x1": 1600,
"y1": 1977,
"x2": 1698,
"y2": 2018,
"text": "25,--",
"text_entropy": 0.1328125
},
{
"id": 203,
"x1": 1705,
"y1": 1979,
"x2": 1732,
"y2": 2014,
"text": "€",
"text_entropy": 0.039306640625
},
{
"id": 204,
"x1": 1477,
"y1": 1616,
"x2": 1695,
"y2": 1662,
"text": "Gymnastik",
"text_entropy": 0.14794921875
},
{
"id": 205,
"x1": 1697,
"y1": 1617,
"x2": 1728,
"y2": 1661,
"text": "/",
"text_entropy": 0.0826416015625
},
{
"id": 206,
"x1": 1734,
"y1": 1615,
"x2": 1891,
"y2": 1655,
"text": "Aerobic",
"text_entropy": 0.12353515625
},
{
"id": 207,
"x1": 1893,
"y1": 1617,
"x2": 1916,
"y2": 1659,
"text": "/",
"text_entropy": 0.10638427734375
},
{
"id": 208,
"x1": 1922,
"y1": 1617,
"x2": 2060,
"y2": 1657,
"text": "Turnen",
"text_entropy": 0.08953857421875
},
{
"id": 209,
"x1": 1484,
"y1": 1712,
"x2": 1527,
"y2": 1750,
"text": "%",
"text_entropy": 0.03375244140625
},
{
"id": 210,
"x1": 1529,
"y1": 1712,
"x2": 1672,
"y2": 1755,
"text": "Beitrag",
"text_entropy": 0.073486328125
},
{
"id": 211,
"x1": 1486,
"y1": 1509,
"x2": 1671,
"y2": 1555,
"text": "(andere)",
"text_entropy": 0.0228118896484375
},
{
"id": 212,
"x1": 1497,
"y1": 2141,
"x2": 1570,
"y2": 2174,
"text": "Die",
"text_entropy": 0.1463623046875
},
{
"id": 213,
"x1": 1572,
"y1": 2140,
"x2": 1728,
"y2": 2182,
"text": "Satzung",
"text_entropy": 0.0787353515625
},
{
"id": 214,
"x1": 1730,
"y1": 2138,
"x2": 1827,
"y2": 2182,
"text": "liegt",
"text_entropy": 0.0606689453125
},
{
"id": 215,
"x1": 1834,
"y1": 2139,
"x2": 2013,
"y2": 2183,
"text": "jederzeit",
"text_entropy": 0.14892578125
},
{
"id": 216,
"x1": 2015,
"y1": 2139,
"x2": 2067,
"y2": 2175,
"text": "im",
"text_entropy": 0.074951171875
},
{
"id": 217,
"x1": 2073,
"y1": 2141,
"x2": 2204,
"y2": 2182,
"text": "Sport-",
"text_entropy": 0.10986328125
},
{
"id": 218,
"x1": 1543,
"y1": 1093,
"x2": 1590,
"y2": 1123,
"text": "W",
"text_entropy": 0.059600830078125
},
{
"id": 219,
"x1": 1578,
"y1": 3093,
"x2": 1804,
"y2": 3136,
"text": "notwendig,",
"text_entropy": 0.10693359375
},
{
"id": 220,
"x1": 1692,
"y1": 1073,
"x2": 1815,
"y2": 1131,
"text": "[X.m",
"text_entropy": 0.2125244140625
},
{
"id": 221,
"x1": 1732,
"y1": 3045,
"x2": 1782,
"y2": 3071,
"text": "zu",
"text_entropy": 0.08746337890625
},
{
"id": 222,
"x1": 1784,
"y1": 3034,
"x2": 1958,
"y2": 3075,
"text": "erfolgen",
"text_entropy": 0.10601806640625
},
{
"id": 223,
"x1": 1965,
"y1": 3034,
"x2": 2040,
"y2": 3070,
"text": "und",
"text_entropy": 0.1239013671875
},
{
"id": 224,
"x1": 1812,
"y1": 1976,
"x2": 1987,
"y2": 2015,
"text": "Familien",
"text_entropy": 0.14599609375
},
{
"id": 225,
"x1": 1989,
"y1": 1976,
"x2": 2090,
"y2": 2019,
"text": "90,--",
"text_entropy": 0.1220703125
},
{
"id": 226,
"x1": 2092,
"y1": 1977,
"x2": 2122,
"y2": 2015,
"text": "€",
"text_entropy": 0.040863037109375
},
{
"id": 227,
"x1": 1815,
"y1": 3093,
"x2": 1877,
"y2": 3128,
"text": "bei",
"text_entropy": 0.04327392578125
},
{
"id": 228,
"x1": 1887,
"y1": 3094,
"x2": 2163,
"y2": 3135,
"text": "Verweigerung",
"text_entropy": 0.102294921875
},
{
"id": 229,
"x1": 1990,
"y1": 1083,
"x2": 2031,
"y2": 1121,
"text": "d",
"text_entropy": 0.002849578857421875
},
{
"id": 230,
"x1": 2051,
"y1": 3036,
"x2": 2101,
"y2": 3069,
"text": "ist",
"text_entropy": 0.1492919921875
},
{
"id": 231,
"x1": 2103,
"y1": 3039,
"x2": 2163,
"y2": 3077,
"text": "je-",
"text_entropy": 0.08807373046875
},
{
"id": 232,
"x1": 2072,
"y1": 1620,
"x2": 2144,
"y2": 1654,
"text": "u.ä.",
"text_entropy": 0.01421356201171875
},
{
"id": 233,
"x1": 2158,
"y1": 212,
"x2": 2173,
"y2": 227,
"text": "|",
"text_entropy": 0.25634765625
},
{
"id": 234,
"x1": 2287,
"y1": 539,
"x2": 2308,
"y2": 555,
"text": "n",
"text_entropy": 0.69091796875
},
{
"id": 235,
"x1": 142,
"y1": 2321,
"x2": 487,
"y2": 2433,
"text": "Musterstadt,",
"text_entropy": 0.058807373046875
},
{
"id": 236,
"x1": 536,
"y1": 2330,
"x2": 901,
"y2": 2411,
"text": "30.12.2022",
"text_entropy": 0.1331787109375
},
{
"id": 237,
"x1": 1246,
"y1": 1146,
"x2": 1343,
"y2": 1225,
"text": "17",
"text_entropy": 0.0027256011962890625
},
{
"id": 238,
"x1": 588,
"y1": 1157,
"x2": 764,
"y2": 1226,
"text": "Zum",
"text_entropy": 0.0098876953125
},
{
"id": 239,
"x1": 787,
"y1": 1140,
"x2": 1136,
"y2": 1235,
"text": "Vereinsheim",
"text_entropy": 0.135009765625
},
{
"id": 240,
"x1": 593,
"y1": 1364,
"x2": 761,
"y2": 1439,
"text": "031",
"text_entropy": 0.052276611328125
},
{
"id": 241,
"x1": 784,
"y1": 1367,
"x2": 1014,
"y2": 1443,
"text": "65432",
"text_entropy": 0.005802154541015625
},
{
"id": 242,
"x1": 1576,
"y1": 1362,
"x2": 1743,
"y2": 1440,
"text": "749.",
"text_entropy": 0.246337890625
},
{
"id": 243,
"x1": 1770,
"y1": 1363,
"x2": 1902,
"y2": 1439,
"text": "151",
"text_entropy": 0.1427001953125
},
{
"id": 244,
"x1": 1929,
"y1": 1363,
"x2": 2163,
"y2": 1445,
"text": "687899",
"text_entropy": 0.0005278587341308594
},
{
"id": 245,
"x1": 669,
"y1": 947,
"x2": 1077,
"y2": 1017,
"text": "Mustermann",
"text_entropy": 0.011993408203125
},
{
"id": 246,
"x1": 604,
"y1": 1050,
"x2": 972,
"y2": 1124,
"text": "13.06.1990",
"text_entropy": 0.10137939453125
},
{
"id": 247,
"x1": 590,
"y1": 1256,
"x2": 819,
"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,
"y1": 2330,
"x2": 1794,
"y2": 2424,
"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"
}
Läd…
Läd…
Custom Extraction Model
You know your document problem best – so why not solve it yourself? Thanks to our Advanced Features, you can create your perfect extraction model. Optimize our pre-trained models on your own data or train your completely individual extraction model.
Custom Extraction Model
You know your document problem best – so why not solve it yourself? Thanks to our Advanced Features, you can create your perfect extraction model. Optimize our pre-trained models on your own data or train your completely individual extraction model.
Your Advantages
Validation
InterfacesSimple verification of the extracted AI data results through the validation interfaces.
InterfacesSimple verification of the extracted AI data results through the validation interfaces.
Individual
WorkflowsWorkflows can be adapted to your specific needs and trained individually.
WorkflowsWorkflows can be adapted to your specific needs and trained individually.
Simple
IntegrationEasy to integrate into existing systems thanks to ready-to-use code snippets.
IntegrationEasy to integrate into existing systems thanks to ready-to-use code snippets.
100% GDPR-
compliantCompliance with all data protection regulations according to GDPR- and Schrems 2.
compliantCompliance with all data protection regulations according to GDPR- and Schrems 2.
Real-time
ProcessingEfficient workflows through fast processing with immediate results in real-time.
ProcessingEfficient workflows through fast processing with immediate results in real-time.
Enterprise-ready
PlatformScalable document processing solution designed for large volumes.
PlatformScalable document processing solution designed for large volumes.
Your Advantages
Validation
InterfacesSimple verification of the extracted AI data results through the validation interfaces.
InterfacesSimple verification of the extracted AI data results through the validation interfaces.
Individual
WorkflowsWorkflows can be adapted to your specific needs and trained individually.
WorkflowsWorkflows can be adapted to your specific needs and trained individually.
Simple
IntegrationEasy to integrate into existing systems thanks to ready-to-use code snippets.
IntegrationEasy to integrate into existing systems thanks to ready-to-use code snippets.
100% GDPR-
compliantCompliance with all data protection regulations according to GDPR- and Schrems 2.
compliantCompliance with all data protection regulations according to GDPR- and Schrems 2.
Real-time
ProcessingEfficient workflows through fast processing with immediate results in real-time.
ProcessingEfficient workflows through fast processing with immediate results in real-time.
Enterprise-ready
PlatformScalable document processing solution designed for large volumes.
PlatformScalable document processing solution designed for large volumes.
Ready For Automation?
Ready For Automation?
Empower your workflow with intelligent document processing and discover our diverse AI solutions.
Contact us now to request your free demo!
Contact us now to request your free demo!