Flower vs Wasabi
Side-by-side comparison of AI visibility scores, market position, and capabilities
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.
Cloud object storage at 80% less than AWS S3 with no egress fees; S3-compatible platform serving 50K+ customers in media, backup, and AI data storage workloads.
About
Wasabi Technologies is a cloud object storage company providing hot cloud storage at approximately 80% less cost than Amazon S3, competing on price, performance, and simplicity for customers who need to store and access large volumes of data in the cloud. Founded in 2015 in Boston, Massachusetts by David Friend and Jeff Flowers (both serial entrepreneurs who previously founded Carbonite), Wasabi has raised approximately $500 million and positioned itself as the lowest-cost alternative to AWS S3, Google Cloud Storage, and Azure Blob Storage for high-volume data storage needs.
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