Hopsworks AI Lakehouse

What Hopsworks AI Lakehouse is

Hopsworks AI Lakehouse is a platform for building batch, real-time, and LLM-based AI systems using open standards. It supports Apache Iceberg, Delta Lake, and Apache Hudi, with feature pipelines that stream to a low-latency serving database and provide sub-second feature freshness. Its Query Service transfers data to Python clients using Arrow and supports temporal joins, pushdown filters, credential vending, and reproducible training data creation. For LLM work, teams can query lakehouse data from prompts, connect vector search for retrieval-augmented generation, and create instruction datasets for fine-tuning while retaining data governance. Feature, training, and inference pipelines cover batch, streaming, real-time, and LLM workflows, and trained models can go to a model registry. Deployment options include managed SaaS, managed Kubernetes on AWS, Azure, or GCP, and air-gapped data centres. A free plan costs nothing and includes one project, Feature Store, Model Registry, and community support; paid tiers are priced on request or usage basis.