Organizations by Tag - recommender-systems: Companies and Projects Building Scalable Recommendation Engines and Production Personalization Platforms
Discover organizations tagged with recommender-systems and explore a curated list of companies, research teams, and open-source projects that build scalable recommendation engines and production personalization platforms. This list highlights technical stacks such as collaborative filtering, matrix factorization, embedding-based and deep learning recommenders, retrieval and hybrid models, plus MLOps and feature engineering patterns for low-latency inference and model retraining. Learn about practical use cases including real-time personalization, CTR optimization, content ranking, and session-based recommendations, and use the filtering UI to narrow results by industry, tech stack, dataset size, model type, or latency requirements. View case studies, architecture diagrams, integration guides, and code samples, compare vendor performance and business impact, and add organizations to your shortlist to find partners and implementation examples that accelerate personalization at scale.
