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Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. Train models on your data in your datastore simply by querying without additional ingestion and pre-processing.
Features
- Build AI applications on top of your datastore
- Turn your existing database into a fully-functional vector database
- Work with any ML/AI frameworks and APIs
- Integrate AI APIs (such as OpenAI) to work together with other models on your data effortlessly.
- Search your data with vector-search, including model management and serving
- Deploy all your AI models to automatically compute outputs (inference) in your datastore in a single environment with simple Python commands
Project Samples
