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Original file line number | Diff line number | Diff line change |
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{ | ||
"id": 30028, | ||
"name": "Gait", | ||
"slug": "gait", | ||
"former_names": [], | ||
"small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7dd4a0ac111eef37a235327e872f43f243700db2.png", | ||
"website": "https://getgait.com", | ||
"all_locations": "San Francisco, CA, USA", | ||
"long_description": "Ever been confused by a block of AI-generated code? Gait is a Cursor and VS Code extension that will let you view the prompt that generated code. Continue off of your coworker's conversations, view analytics on your AI codegen use, and more!", | ||
"one_liner": "Building Dev Infra for AI Software Engineers", | ||
"team_size": 2, | ||
"industry": "B2B", | ||
"subindustry": "B2B", | ||
"launched_at": 1728969633, | ||
"tags": [ | ||
"Developer Tools", | ||
"AI" | ||
], | ||
"tags_highlighted": [], | ||
"top_company": false, | ||
"isHiring": false, | ||
"nonprofit": false, | ||
"batch": "F24", | ||
"status": "Active", | ||
"industries": [ | ||
"B2B" | ||
], | ||
"regions": [ | ||
"United States of America", | ||
"America / Canada" | ||
], | ||
"stage": "Early", | ||
"app_video_public": false, | ||
"demo_day_video_public": false, | ||
"app_answers": null, | ||
"question_answers": true, | ||
"url": "https://www.ycombinator.com/companies/gait", | ||
"api": "https://yc-oss.github.io/api/batches/f24/gait.json" | ||
} |
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{ | ||
"id": 30087, | ||
"name": "Gecko Security", | ||
"slug": "gecko-security", | ||
"former_names": [ | ||
"Gecko Security Inc." | ||
], | ||
"small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6cb5e156a2d833200fe0f915ffe682c440528c6a.png", | ||
"website": "https://gecko.security", | ||
"all_locations": "San Francisco, CA, USA", | ||
"long_description": "We built Gecko for teams that want to build secure code quickly without wasting time on security tools that don’t deliver results, or relying on one-time human pentests that quickly become outdated. Gecko uses AI to understand how your application should work, simulates relevant attacks to find critical vulnerabilities, and then verifies these vulnerabilities by exploiting them. It also helps you understand the risk of these vulnerabilities and applies a working fix to keep your code secure.", | ||
"one_liner": "AI Security Engineer to Find and Fix Vulnerabilities ", | ||
"team_size": 2, | ||
"industry": "B2B", | ||
"subindustry": "B2B -> Security", | ||
"launched_at": 1729014786, | ||
"tags": [ | ||
"Artificial Intelligence", | ||
"SaaS", | ||
"B2B", | ||
"Security", | ||
"Cybersecurity" | ||
], | ||
"tags_highlighted": [], | ||
"top_company": false, | ||
"isHiring": false, | ||
"nonprofit": false, | ||
"batch": "F24", | ||
"status": "Active", | ||
"industries": [ | ||
"B2B", | ||
"Security" | ||
], | ||
"regions": [ | ||
"United States of America", | ||
"America / Canada", | ||
"Remote", | ||
"Partly Remote" | ||
], | ||
"stage": "Early", | ||
"app_video_public": false, | ||
"demo_day_video_public": false, | ||
"app_answers": null, | ||
"question_answers": false, | ||
"url": "https://www.ycombinator.com/companies/gecko-security", | ||
"api": "https://yc-oss.github.io/api/batches/f24/gecko-security.json" | ||
} |
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{ | ||
"id": 30103, | ||
"name": "Metreecs", | ||
"slug": "metreecs", | ||
"former_names": [], | ||
"small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/69c12f5f2e6e61b0c27a8363a971af3307f489c2.png", | ||
"website": "https://www.metreecs.com", | ||
"all_locations": "Paris, Île-de-France, France", | ||
"long_description": "Metreecs helps retailers plan, buy, and allocate products using AI-demand forecasting. We prevent overstock and out-of-stock situations, allowing clients to eliminate waste, free up capital, and drive higher sales.", | ||
"one_liner": "AI-powered demand forecasting for retail", | ||
"team_size": 3, | ||
"industry": "B2B", | ||
"subindustry": "B2B -> Retail", | ||
"launched_at": 1729012958, | ||
"tags": [ | ||
"Artificial Intelligence", | ||
"Supply Chain", | ||
"Retail Tech" | ||
], | ||
"tags_highlighted": [], | ||
"top_company": false, | ||
"isHiring": false, | ||
"nonprofit": false, | ||
"batch": "F24", | ||
"status": "Active", | ||
"industries": [ | ||
"B2B", | ||
"Retail" | ||
], | ||
"regions": [ | ||
"France", | ||
"Europe" | ||
], | ||
"stage": "Early", | ||
"app_video_public": false, | ||
"demo_day_video_public": false, | ||
"app_answers": null, | ||
"question_answers": false, | ||
"url": "https://www.ycombinator.com/companies/metreecs", | ||
"api": "https://yc-oss.github.io/api/batches/f24/metreecs.json" | ||
} |
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Original file line number | Diff line number | Diff line change |
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{ | ||
"id": 30117, | ||
"name": "Relvy AI", | ||
"slug": "relvy-ai", | ||
"former_names": [], | ||
"small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2aa06b2c04632ad68c2151cc3aac66c942a0119b.png", | ||
"website": "https://www.relvy.ai", | ||
"all_locations": "Palo Alto, CA, USA", | ||
"long_description": "Relvy automates troubleshooting of production software. Engineers can get started with Relvy's lightweight debugging language model in less than 5 minutes, and save 30 minutes of triaging time per on-call alert.", | ||
"one_liner": "AI for debugging production issues", | ||
"team_size": 3, | ||
"industry": "B2B", | ||
"subindustry": "B2B -> Engineering, Product and Design", | ||
"launched_at": 1729032291, | ||
"tags": [ | ||
"Artificial Intelligence", | ||
"Developer Tools", | ||
"SaaS" | ||
], | ||
"tags_highlighted": [], | ||
"top_company": false, | ||
"isHiring": false, | ||
"nonprofit": false, | ||
"batch": "F24", | ||
"status": "Active", | ||
"industries": [ | ||
"B2B", | ||
"Engineering, Product and Design" | ||
], | ||
"regions": [ | ||
"United States of America", | ||
"America / Canada" | ||
], | ||
"stage": "Early", | ||
"app_video_public": false, | ||
"demo_day_video_public": false, | ||
"app_answers": null, | ||
"question_answers": false, | ||
"url": "https://www.ycombinator.com/companies/relvy-ai", | ||
"api": "https://yc-oss.github.io/api/batches/f24/relvy-ai.json" | ||
} |
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Original file line number | Diff line number | Diff line change |
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{ | ||
"id": 30125, | ||
"name": "Synth", | ||
"slug": "synth-3", | ||
"former_names": [], | ||
"small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/72c8ca1f80fbcb63a0a616d53bce31153601a954.png", | ||
"website": "https://www.usesynth.ai", | ||
"all_locations": "", | ||
"long_description": "You add a few decorators to your agent code, and run your agent on a dataset of questions you've generated / collected in the wild. We give you back a dataset of message triplets that's ready to be uploaded to your fine-tuning provider of choice (OpenAI, OpenPipe, Anthropic, Gemini, etc) that will give you a language model ready to steer your agent in production more effectively.", | ||
"one_liner": "We help AI agents learn from data.", | ||
"team_size": 1, | ||
"industry": "B2B", | ||
"subindustry": "B2B -> Infrastructure", | ||
"launched_at": 1729021221, | ||
"tags": [ | ||
"Artificial Intelligence", | ||
"Reinforcement Learning", | ||
"Infrastructure" | ||
], | ||
"tags_highlighted": [], | ||
"top_company": false, | ||
"isHiring": false, | ||
"nonprofit": false, | ||
"batch": "F24", | ||
"status": "Active", | ||
"industries": [ | ||
"B2B", | ||
"Infrastructure" | ||
], | ||
"regions": [ | ||
"Unspecified" | ||
], | ||
"stage": "Early", | ||
"app_video_public": false, | ||
"demo_day_video_public": false, | ||
"app_answers": null, | ||
"question_answers": false, | ||
"url": "https://www.ycombinator.com/companies/synth-3", | ||
"api": "https://yc-oss.github.io/api/batches/f24/synth-3.json" | ||
} |
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