Reworkd vs Flower
Side-by-side comparison of AI visibility scores, market position, and capabilities
SF YC S23 multimodal LLM web scraping agents extracting structured data from thousands of sites; $4M total (Paul Graham/Nat Friedman/General Catalyst seed 2024) by AgentGPT team competing with Apify and Bright Data for AI-powered enterprise web da...
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Reworkd is a San Francisco-based AI web data extraction company — backed by Y Combinator (S23) with $4 million in total funding including a $2.75 million seed round in 2024 from Paul Graham, Nat Friedman, Daniel Gross, SV Angel, General Catalyst, and Panache Ventures, following a $1.25 million pre-seed from YC in 2023 — providing data engineering teams, AI researchers, and enterprise data operations with multimodal LLM-powered agents that autonomously extract structured data from thousands of websites at scale. Founded in 2023, Reworkd previously built AgentGPT (a viral autonomous AI agent platform that reached 100,000+ daily users), then pivoted to enterprise web scraping as the more commercially durable application of autonomous AI agents for data extraction workflows.
SF YC W23 most popular open-source federated learning framework for privacy-preserving AI training; $20M Felicis Series A Feb 2024 serving Mozilla/Samsung/Bosch/Banking Circle competing with TensorFlow Federated for distributed training without ce...
About
Flower is a San Francisco-based open-source federated learning framework company — backed by Y Combinator (W23) with $20 million in Series A funding in February 2024 led by Felicis Ventures with participation from First Spark Ventures, Mozilla Ventures, and angel investors including Clement Delangue (Hugging Face CEO), Scott Chacon (GitHub co-founder), and founders of Factorial and Betaworks — providing organizations, researchers, and developers with the world's most popular federated learning platform for training AI models on distributed data sources while maintaining data privacy and regulatory compliance, serving enterprise customers including Mozilla, Samsung, Bosch, Banking Circle, and Temenos. Founded in 2022, Flower enables organizations to train high-quality AI models across distributed datasets (patient records at multiple hospitals, financial transaction data across banks, user behavior data on user devices) without centralizing sensitive data into a single training environment.
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