Hopsworks is an AI lakehouse for data and ML teams that need real-time pipelines. It combines an enterprise feature store with RonDB to support millisecond-level serving for online ML and LLM workloads.
Real-time ML and LLM use cases
Hopsworks connects streaming data, warehouses, and databases, then serves fresh features to models with very low latency. Common scenarios include:
- Fraud detection and risk scoring
- Recommendations and ranking
- Personalization and other online decisioning
Unified feature and data layer
The platform brings together a data lake, data warehouse, and operational databases around a single feature store. This helps teams:
- Reuse features across projects
- Reduce duplicated pipelines and definitions
- Improve data quality control for model inputs
GPU management and production deployment
Hopsworks supports managing GPU resources for LLMs and other models, scaling compute, and speeding up the path to production. It also supports multiple frameworks and programming languages to reduce lock-in to a specific stack.
