Hopsworks

Hopsworks is a unified platform for feature engineering, real-time ML, and production AI systems.

Description

Hopsworks is a unified SaaS platform designed for building, deploying, and running production AI systems. It integrates feature engineering, real-time machine learning, and MLOps capabilities into a single environment. The platform offers a feature store with sub-millisecond latency for efficient feature retrieval and reuse, an AI lakehouse that supports open data formats like Delta, Iceberg, and Hudi for faster reads, and comprehensive MLOps tools for managing the entire model lifecycle from experimentation to deployment. It emphasizes scalability, supporting frameworks such as Spark, Flink, and Pandas, and provides GPU management for training and serving LLMs. Trusted by leading organizations, Hopsworks enables teams to streamline AI development while maintaining data sovereignty and control.

Features

• Feature Store with sub-millisecond latency powered by RonDB for central feature data management and reuse
• AI Lakehouse supporting Delta, Iceberg, and Hudi tables with Python-native query engine for faster data reads
• MLOps Platform for end-to-end lifecycle management including experiment tracking, model registry, and deployment pipelines
• Real-time AI capabilities with low-latency inference and support for frameworks like Spark, Flink, and Pandas
• GPU and compute management for scalable training and serving of LLMs and other ML models
• Sovereign AI options for air-gapped, on-premises, or hybrid deployments with full data control
• Modular and scalable architecture allowing startups to large enterprises to handle petabyte-scale data

Benefits

• Reduces development costs by up to 80% through feature reuse and streamlined workflows
• Accelerates deployment with 10x faster model deployment compared to traditional methods
• Enhances performance with 9-45x faster data reads and best-in-class feature freshness
• Improves efficiency with unified tools for feature engineering, real-time ML, and MLOps, reducing training-production skew
• Provides flexibility with support for open data formats and multiple frameworks, avoiding vendor lock-in
• Ensures data sovereignty and security with options for on-premises or hybrid deployments
• Scales seamlessly from small projects to enterprise-level AI systems with petabyte data handling

Links

• Home: https://www.hopsworks.ai