Discover what Cleora.ai is and how it creates fast, scalable enterprise embeddings for recommendations, segmentation, and behavioral prediction.

Cleora.ai is a machine learning tool that helps Data Science and Analytics teams create high-quality enterprise embeddings without expensive hardware. It embeds entities such as customers, products, and other business data into n-dimensional spaces using a stable, iterative projection method. The resulting embeddings capture an entity’s behavioral history as large-scale graphs, enabling advanced models for recommender systems, customer segmentation, behavior prediction, and customer lifetime value modeling. To get started, you only need three columns from your databases.
Cleora is fast, efficient, and inductive, meaning it can compute vectors for new entities based on their interactions. It can also combine embeddings from different datasets. The PRO version adds automatic scaling, better performance, and higher embedding quality without requiring costly hardware.
Cleora is up to 200 times faster than DeepWalk and 4x–8x faster than Facebook’s PyTorch-BigGraph. It can process billion-scale graph data efficiently — for example, it processed National Capital Region graph data in under 5 minutes.
Cleora.ai was developed by Sair, a lab focused on behavioral modeling, recommendations, and large-scale data processing. Its goal is to make high-quality enterprise embeddings efficient and affordable by removing the hardware barrier. Both a PRO version for enterprises and an Open Source version on GitHub are available.
Cleora.ai supports a range of applications, including:
Cleora.ai is designed for professionals working with data and machine learning, particularly data scientists and analytics teams who need fast, scalable embeddings without investing in specialized hardware.
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