In the talk we discuss why we think the community needs SuperDuperDB, introduce it’s design principles and show how to build AI-data products more efficiently and flexibly than ever before.

SuperDuperDB is an open source Python package providing tools for developers to apply AI and machine learning on top of their existing data stores. Developers and data scientists continue to use their preferred tools, avoiding both data migration and duplication to specialized data stores. They also have the freedom to run SuperDuperDB anywhere, avoiding lock-in to any one AI ecosystem.

With SuperDuperDB developers can:
- Deploy their chosen AI models to automatically compute outputs (inference) in their datastore in a single environment with simple Python commands.
- Train models on their data simply by querying without additional ingestion and pre-processing.
- Integrate AI APIs (such as OpenAI) to work together with other models on their data effortlessly.
- Search data with vector-search, including model management and serving.