Y Combinator Extractor
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Pricing
$30.00/month + usage
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Y Combinator Extractor
Under maintenance
💫 All-In-One YCombinator.com Scraper
0.0 (0)
Pricing
$30.00/month + usage
3
Monthly users
14
Runs succeeded
49%
Response time
34 days
Last modified
5 days ago
You can access the Y Combinator Extractor programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
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705 "Industrial",
706 "Industrials",
707 "Agriculture",
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709 "Aviation and Space",
710 "Climate",
711 "Drones",
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714 "Real Estate and Construction",
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717 "Unspecified"
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722 "B2B -> Engineering, Product and Design",
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724 "B2B -> Human Resources",
725 "B2B -> Infrastructure",
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727 "B2B -> Marketing",
728 "B2B -> Office Management",
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740 "Consumer -> Food and Beverage",
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847 "Lithuania",
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853 "Netherlands",
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858 "Panama",
859 "Peru",
860 "Philippines",
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863 "Puerto Rico",
864 "Qatar",
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866 "Saudi Arabia",
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870 "Slovenia",
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872 "South Korea",
873 "Spain",
874 "Sweden",
875 "Switzerland",
876 "Taiwan",
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878 "Thailand",
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881 "Ukraine",
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885 "United States of America",
886 "Unspecified",
887 "Uruguay",
888 "Vietnam"
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919 "W2014",
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923 "W2019",
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975 "Augmented Reality",
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978 "Automotive",
979 "Autonomous Trucking",
980 "B2B",
981 "Banking as a Service",
982 "Big Data",
983 "Billing",
984 "Biometrics",
985 "Bioplastic",
986 "Biotech",
987 "Biotechnology",
988 "CRISPR",
989 "CRM",
990 "Calendar",
991 "Call Center",
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993 "Careers",
994 "Cell Therapy",
995 "Chat",
996 "Chatbot",
997 "Civic Tech",
998 "Climate",
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1000 "Cloud Computing",
1001 "Collaboration",
1002 "Commercial Space Launch",
1003 "Community",
1004 "Compliance",
1005 "Computer Vision",
1006 "Construction",
1007 "Consumer",
1008 "Consumer Finance",
1009 "Consumer Health Services",
1010 "Consumer Products",
1011 "Conversational AI",
1012 "Conversational Banking",
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1014 "Crowdfunding",
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1020 "Customer Support",
1021 "Cybersecurity",
1022 "Data Engineering",
1023 "Data Labeling",
1024 "Data Science",
1025 "Data Visualization",
1026 "Databases",
1027 "Dating",
1028 "DeFi",
1029 "Deep Learning",
1030 "Delivery",
1031 "Dental",
1032 "Design",
1033 "Design Tools",
1034 "DevOps",
1035 "DevSecOps",
1036 "Developer Tools",
1037 "Diagnostics",
1038 "Digital Health",
1039 "Diversity & Inclusion",
1040 "Documents",
1041 "Drones",
1042 "Drug Delivery",
1043 "Drug discovery",
1044 "E-commerce",
1045 "Edge Computing Semiconductors",
1046 "Edtech",
1047 "Education",
1048 "Electric Vehicles",
1049 "Electronics",
1050 "Email",
1051 "Emerging Markets",
1052 "Energy",
1053 "Energy Storage",
1054 "Enterprise",
1055 "Enterprise Software",
1056 "Entertainment",
1057 "Fashion",
1058 "Feedback",
1059 "Femtech",
1060 "FinOps",
1061 "Finance",
1062 "Fintech",
1063 "Fitness",
1064 "Food",
1065 "Food & Beverage",
1066 "Food Tech",
1067 "Fraud Detection",
1068 "Fraud Prevention",
1069 "Fundraising",
1070 "Gaming",
1071 "Gene Therapy",
1072 "Generative AI",
1073 "Genetic Engineering",
1074 "Genomics",
1075 "Geographic Information System",
1076 "Ghost Kitchens",
1077 "GovTech",
1078 "GraphQL",
1079 "Grocery",
1080 "HR Tech",
1081 "Hard Tech",
1082 "Hardware",
1083 "Health & Wellness",
1084 "Health Insurance",
1085 "Health Tech",
1086 "Healthcare",
1087 "Healthcare IT",
1088 "Home Automation",
1089 "Home Services",
1090 "Housing",
1091 "Human Resources",
1092 "Hydrogen Energy",
1093 "Identity",
1094 "Immigration",
1095 "Income Share Agreements",
1096 "India",
1097 "Industrial",
1098 "Infrastructure",
1099 "Insurance",
1100 "International",
1101 "Investing",
1102 "Investments",
1103 "IoT",
1104 "Kubernetes",
1105 "Latin America",
1106 "Legal",
1107 "LegalTech",
1108 "Lending",
1109 "Lidar",
1110 "Logistics",
1111 "ML",
1112 "Machine Learning",
1113 "Manufacturing",
1114 "Market Research",
1115 "Marketing",
1116 "Marketplace",
1117 "Media",
1118 "Medical Devices",
1119 "Medical Robotics",
1120 "Mental Health",
1121 "Mental Health Tech",
1122 "Messaging",
1123 "Metaverse",
1124 "Microfluidics",
1125 "Mining",
1126 "Monitoring",
1127 "Music",
1128 "NFT",
1129 "NLP",
1130 "Nanomedicine",
1131 "Nanosensors",
1132 "Nanotechnology",
1133 "Navigation",
1134 "Neobank",
1135 "Neurotechnology",
1136 "No-code",
1137 "Note-taking",
1138 "Oncology",
1139 "Open Source",
1140 "Operations",
1141 "Payments",
1142 "Payroll",
1143 "Podcasts",
1144 "Primary Care",
1145 "Privacy",
1146 "Procurement",
1147 "Productivity",
1148 "Proptech",
1149 "Quantum Computing",
1150 "Real Estate",
1151 "Recommendation System",
1152 "Recruiting",
1153 "Regtech",
1154 "Reinforcement Learning",
1155 "Remittances",
1156 "Remote Work",
1157 "Renewable Energy",
1158 "Restaurant Tech",
1159 "Retail",
1160 "Retail Tech",
1161 "Reviews",
1162 "Ridesharing",
1163 "Robotic Process Automation",
1164 "Robotic Surgery",
1165 "Robotics",
1166 "Rocketry",
1167 "SEO",
1168 "SMB",
1169 "SMS",
1170 "SaaS",
1171 "Sales",
1172 "Sales Enablement",
1173 "Satellites",
1174 "Scheduling",
1175 "Search",
1176 "Security",
1177 "Semiconductors",
1178 "Sleep Tech",
1179 "Social",
1180 "Social Media",
1181 "Social Network",
1182 "Solar Power",
1183 "Space Exploration",
1184 "Sports Tech",
1185 "Stocks",
1186 "Subscriptions",
1187 "Supply Chain",
1188 "Sustainability",
1189 "Sustainable Agriculture",
1190 "Sustainable Fashion",
1191 "Sustainable Tourism",
1192 "Swarm Robotics",
1193 "Synthetic Biology",
1194 "Talent Acquisition",
1195 "Team Collaboration",
1196 "Telecommunications",
1197 "Telehealth",
1198 "Telemedicine",
1199 "Therapeutics",
1200 "Ticketing",
1201 "Time Series",
1202 "Trading",
1203 "Transportation",
1204 "Travel",
1205 "Trust & Safety",
1206 "Unmanned Vehicle",
1207 "Video",
1208 "Virtual Reality",
1209 "Warehouse Management Tech",
1210 "Weather",
1211 "Web Development",
1212 "Women's Health",
1213 "Workflow Automation",
1214 "eLearning",
1215 "eSports"
1216 ]
1217 }
1218 },
1219 "library:media": {
1220 "title": "Media Type",
1221 "type": "array",
1222 "description": "",
1223 "items": {
1224 "type": "string",
1225 "enum": [
1226 "Blog",
1227 "External",
1228 "Video"
1229 ]
1230 }
1231 },
1232 "library:categories": {
1233 "title": "Categories",
1234 "type": "array",
1235 "description": "",
1236 "items": {
1237 "type": "string",
1238 "enum": [
1239 "Becoming a Founder",
1240 "Academia to Startup",
1241 "College Students",
1242 "Non-Technical Founders",
1243 "Business Models",
1244 "Monetization",
1245 "Pricing",
1246 "Unit Economics",
1247 "Co-Founders",
1248 "B2B",
1249 "Consumer",
1250 "Real Estate",
1251 "Science + Biotech",
1252 "Company Stages",
1253 "Early Stage",
1254 "Growth Stage",
1255 "Pivoting",
1256 "Staying Alive",
1257 "Customers",
1258 "Product Market Fit",
1259 "Retention",
1260 "Talking to Users",
1261 "Design",
1262 "UX + Design",
1263 "Finance",
1264 "Cash Burn",
1265 "Founder Psychology",
1266 "Decision Making",
1267 "Mental Health",
1268 "Motivation",
1269 "Time Management",
1270 "Founder Stories",
1271 "Women Founders",
1272 "Fundraising + Investors",
1273 "Board Management",
1274 "Fundraising",
1275 "Fundraising Docs",
1276 "Investors",
1277 "Negotiation",
1278 "Pitch Deck",
1279 "Safes",
1280 "Seed Round",
1281 "Series A",
1282 "Valuations",
1283 "Getting Started",
1284 "Growth",
1285 "Enterprise Sales",
1286 "KPI",
1287 "Launch",
1288 "Marketing",
1289 "Press",
1290 "China",
1291 "Legal",
1292 "Management",
1293 "CEO",
1294 "CTO",
1295 "Leadership",
1296 "Office Hours",
1297 "People",
1298 "Advisers",
1299 "Compensation",
1300 "Culture",
1301 "Diversity + Inclusion",
1302 "Hiring",
1303 "Recruiting",
1304 "Stock Equity",
1305 "Product",
1306 "Building Product",
1307 "Experimentation",
1308 "Feature Prioritization",
1309 "MVP",
1310 "Startup Ideas",
1311 "Problems to Solve",
1312 "Technical",
1313 "Artificial Intelligence",
1314 "Engineering",
1315 "Working at a Startup",
1316 "YC",
1317 "Applying to YC",
1318 "YC Demo Day"
1319 ],
1320 "enumTitles": [
1321 "Becoming a Founder",
1322 "Becoming a Founder -> Academia to Startup",
1323 "Becoming a Founder -> College Students",
1324 "Becoming a Founder -> Non-Technical Founders",
1325 "Business Models",
1326 "Business Models -> Monetization",
1327 "Business Models -> Pricing",
1328 "Business Models -> Unit Economics",
1329 "Co-Founders",
1330 "Company Categories -> B2B",
1331 "Company Categories -> Consumer",
1332 "Company Categories -> Real Estate",
1333 "Company Categories -> Science + Biotech",
1334 "Company Stages",
1335 "Company Stages -> Early Stage",
1336 "Company Stages -> Growth Stage",
1337 "Company Stages -> Pivoting",
1338 "Company Stages -> Staying Alive",
1339 "Customers",
1340 "Customers -> Product Market Fit",
1341 "Customers -> Retention",
1342 "Customers -> Talking to Users",
1343 "Design",
1344 "Design -> UX + Design",
1345 "Finance",
1346 "Finance -> Cash Burn",
1347 "Founder Psychology",
1348 "Founder Psychology -> Decision Making",
1349 "Founder Psychology -> Mental Health",
1350 "Founder Psychology -> Motivation",
1351 "Founder Psychology -> Time Management",
1352 "Founder Stories",
1353 "Founder Stories -> Women Founders",
1354 "Fundraising + Investors",
1355 "Fundraising + Investors -> Board Management",
1356 "Fundraising + Investors -> Fundraising",
1357 "Fundraising + Investors -> Fundraising Docs",
1358 "Fundraising + Investors -> Investors",
1359 "Fundraising + Investors -> Negotiation",
1360 "Fundraising + Investors -> Pitch Deck",
1361 "Fundraising + Investors -> Safes",
1362 "Fundraising + Investors -> Seed Round",
1363 "Fundraising + Investors -> Series A",
1364 "Fundraising + Investors -> Valuations",
1365 "Getting Started",
1366 "Growth",
1367 "Growth -> Enterprise Sales",
1368 "Growth -> KPI",
1369 "Growth -> Launch",
1370 "Growth -> Marketing",
1371 "Growth -> Press",
1372 "International -> China",
1373 "Legal",
1374 "Management",
1375 "Management -> CEO",
1376 "Management -> CTO",
1377 "Management -> Leadership",
1378 "Office Hours",
1379 "People",
1380 "People -> Advisers",
1381 "People -> Compensation",
1382 "People -> Culture",
1383 "People -> Diversity + Inclusion",
1384 "People -> Hiring",
1385 "People -> Recruiting",
1386 "People -> Stock Equity",
1387 "Product",
1388 "Product -> Building Product",
1389 "Product -> Experimentation",
1390 "Product -> Feature Prioritization",
1391 "Product -> MVP",
1392 "Startup Ideas",
1393 "Startup Ideas -> Problems to Solve",
1394 "Technical",
1395 "Technical -> Artificial Intelligence",
1396 "Technical -> Engineering",
1397 "Working at a Startup",
1398 "YC",
1399 "YC -> Applying to YC",
1400 "YC -> YC Demo Day"
1401 ]
1402 }
1403 },
1404 "dev_custom_headers": {
1405 "title": "📜 HTTP HEADERS",
1406 "type": "array",
1407 "description": "💡 Additional HTTP Headers",
1408 "items": {
1409 "type": "object",
1410 "required": [
1411 "key",
1412 "value"
1413 ],
1414 "properties": {
1415 "key": {
1416 "type": "string",
1417 "title": "Key"
1418 },
1419 "value": {
1420 "type": "string",
1421 "title": "Value"
1422 }
1423 }
1424 }
1425 },
1426 "dev_custom_cookies": {
1427 "title": "🍰 HTTP COOKIES",
1428 "type": "array",
1429 "description": "💡 Additional HTTP Cookies",
1430 "items": {
1431 "type": "object",
1432 "required": [
1433 "key",
1434 "value"
1435 ],
1436 "properties": {
1437 "key": {
1438 "type": "string",
1439 "title": "Key"
1440 },
1441 "value": {
1442 "type": "string",
1443 "title": "Value"
1444 }
1445 }
1446 }
1447 },
1448 "dev_transform_fields": {
1449 "title": "♻️ CUSTOM FIELD",
1450 "type": "array",
1451 "description": "💡 <b>Transform the resulting output. Select only needed fields.</b><br><br>For nested object use <b>DOT</b>. For example: <pre>address.streetAddress</pre><br>For nested array use <b>NUMBER</b> <i>(index of array element starting from index=0)</i>. For example: <pre>images.0.url</pre>",
1452 "items": {
1453 "type": "object",
1454 "required": [
1455 "key",
1456 "value"
1457 ],
1458 "properties": {
1459 "key": {
1460 "type": "string",
1461 "title": "Key"
1462 },
1463 "value": {
1464 "type": "string",
1465 "title": "Value"
1466 }
1467 }
1468 }
1469 },
1470 "dev_dataset_name": {
1471 "title": "📁 CUSTOM STORAGE",
1472 "type": "string",
1473 "description": "💡 <b>Save results into custom named Dataset, use mask to customize dataset name</b><br><br><code>{ACTOR} = actor name<br>{DATE} = date (YYYYMMDD)<br>{TIME} = time (HHMMSS)</code><br><br>This masks can be used to autogenerate Dataset Name.<br><br>example: <i><code>data-{DATE}</code></i><br>Depending on today date the dataset name will be: <code>data-20230603</code><i><br><br>default: <code>data-{ACTOR}-{DATE}-{TIME}</code></i>"
1474 },
1475 "dev_dataset_clear": {
1476 "title": "Clear Storage",
1477 "type": "boolean",
1478 "description": "Clear Dataset before insert/update."
1479 },
1480 "dev_no_strip": {
1481 "title": "Disable data cleansing",
1482 "type": "boolean",
1483 "description": "💡 Keep/Save empty values <i><code>(NULL, FALSE, empty ARRAY, empty OBJECT, empty STRING)</code></i>"
1484 }
1485 }
1486 },
1487 "runsResponseSchema": {
1488 "type": "object",
1489 "properties": {
1490 "data": {
1491 "type": "object",
1492 "properties": {
1493 "id": {
1494 "type": "string"
1495 },
1496 "actId": {
1497 "type": "string"
1498 },
1499 "userId": {
1500 "type": "string"
1501 },
1502 "startedAt": {
1503 "type": "string",
1504 "format": "date-time",
1505 "example": "2025-01-08T00:00:00.000Z"
1506 },
1507 "finishedAt": {
1508 "type": "string",
1509 "format": "date-time",
1510 "example": "2025-01-08T00:00:00.000Z"
1511 },
1512 "status": {
1513 "type": "string",
1514 "example": "READY"
1515 },
1516 "meta": {
1517 "type": "object",
1518 "properties": {
1519 "origin": {
1520 "type": "string",
1521 "example": "API"
1522 },
1523 "userAgent": {
1524 "type": "string"
1525 }
1526 }
1527 },
1528 "stats": {
1529 "type": "object",
1530 "properties": {
1531 "inputBodyLen": {
1532 "type": "integer",
1533 "example": 2000
1534 },
1535 "rebootCount": {
1536 "type": "integer",
1537 "example": 0
1538 },
1539 "restartCount": {
1540 "type": "integer",
1541 "example": 0
1542 },
1543 "resurrectCount": {
1544 "type": "integer",
1545 "example": 0
1546 },
1547 "computeUnits": {
1548 "type": "integer",
1549 "example": 0
1550 }
1551 }
1552 },
1553 "options": {
1554 "type": "object",
1555 "properties": {
1556 "build": {
1557 "type": "string",
1558 "example": "latest"
1559 },
1560 "timeoutSecs": {
1561 "type": "integer",
1562 "example": 300
1563 },
1564 "memoryMbytes": {
1565 "type": "integer",
1566 "example": 1024
1567 },
1568 "diskMbytes": {
1569 "type": "integer",
1570 "example": 2048
1571 }
1572 }
1573 },
1574 "buildId": {
1575 "type": "string"
1576 },
1577 "defaultKeyValueStoreId": {
1578 "type": "string"
1579 },
1580 "defaultDatasetId": {
1581 "type": "string"
1582 },
1583 "defaultRequestQueueId": {
1584 "type": "string"
1585 },
1586 "buildNumber": {
1587 "type": "string",
1588 "example": "1.0.0"
1589 },
1590 "containerUrl": {
1591 "type": "string"
1592 },
1593 "usage": {
1594 "type": "object",
1595 "properties": {
1596 "ACTOR_COMPUTE_UNITS": {
1597 "type": "integer",
1598 "example": 0
1599 },
1600 "DATASET_READS": {
1601 "type": "integer",
1602 "example": 0
1603 },
1604 "DATASET_WRITES": {
1605 "type": "integer",
1606 "example": 0
1607 },
1608 "KEY_VALUE_STORE_READS": {
1609 "type": "integer",
1610 "example": 0
1611 },
1612 "KEY_VALUE_STORE_WRITES": {
1613 "type": "integer",
1614 "example": 1
1615 },
1616 "KEY_VALUE_STORE_LISTS": {
1617 "type": "integer",
1618 "example": 0
1619 },
1620 "REQUEST_QUEUE_READS": {
1621 "type": "integer",
1622 "example": 0
1623 },
1624 "REQUEST_QUEUE_WRITES": {
1625 "type": "integer",
1626 "example": 0
1627 },
1628 "DATA_TRANSFER_INTERNAL_GBYTES": {
1629 "type": "integer",
1630 "example": 0
1631 },
1632 "DATA_TRANSFER_EXTERNAL_GBYTES": {
1633 "type": "integer",
1634 "example": 0
1635 },
1636 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
1637 "type": "integer",
1638 "example": 0
1639 },
1640 "PROXY_SERPS": {
1641 "type": "integer",
1642 "example": 0
1643 }
1644 }
1645 },
1646 "usageTotalUsd": {
1647 "type": "number",
1648 "example": 0.00005
1649 },
1650 "usageUsd": {
1651 "type": "object",
1652 "properties": {
1653 "ACTOR_COMPUTE_UNITS": {
1654 "type": "integer",
1655 "example": 0
1656 },
1657 "DATASET_READS": {
1658 "type": "integer",
1659 "example": 0
1660 },
1661 "DATASET_WRITES": {
1662 "type": "integer",
1663 "example": 0
1664 },
1665 "KEY_VALUE_STORE_READS": {
1666 "type": "integer",
1667 "example": 0
1668 },
1669 "KEY_VALUE_STORE_WRITES": {
1670 "type": "number",
1671 "example": 0.00005
1672 },
1673 "KEY_VALUE_STORE_LISTS": {
1674 "type": "integer",
1675 "example": 0
1676 },
1677 "REQUEST_QUEUE_READS": {
1678 "type": "integer",
1679 "example": 0
1680 },
1681 "REQUEST_QUEUE_WRITES": {
1682 "type": "integer",
1683 "example": 0
1684 },
1685 "DATA_TRANSFER_INTERNAL_GBYTES": {
1686 "type": "integer",
1687 "example": 0
1688 },
1689 "DATA_TRANSFER_EXTERNAL_GBYTES": {
1690 "type": "integer",
1691 "example": 0
1692 },
1693 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
1694 "type": "integer",
1695 "example": 0
1696 },
1697 "PROXY_SERPS": {
1698 "type": "integer",
1699 "example": 0
1700 }
1701 }
1702 }
1703 }
1704 }
1705 }
1706 }
1707 }
1708 }
1709}Y Combinator Extractor OpenAPI definition
OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Y Combinator Extractor from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients:
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Pricing model
RentalTo use this Actor, you have to pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period. You also pay for the Apify platform usage.
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7 days
Price
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