DataRobot Vector Databases (GenAI)
A premium vector database capability within the DataRobot Generative AI platform that stores chunked unstructured text and their embeddings for retrieval-augmented generation (RAG). Users can create vector database objects, connect supported data sources from the DataRobot Data Registry, configure embeddings and chunking, and attach these vector databases to LLM blueprints in the playground to ground model responses in proprietary data.
About this tool
DataRobot Vector Databases (GenAI)
Overview
DataRobot Vector Databases (GenAI) is a premium capability within the DataRobot Generative AI platform for storing chunked unstructured text and their embeddings to support retrieval-augmented generation (RAG). It lets users ground large language model (LLM) responses in their own proprietary data by connecting data sources, configuring embeddings and chunking, and attaching vector databases to LLM blueprints.
Key Facts
- Category: Managed vector databases
- Vendor / Brand: DataRobot
- Product type: Cloud GenAI / RAG data layer inside the DataRobot AI Platform
- Typical use cases: RAG applications, enterprise knowledge search, grounding LLMs with proprietary content
Features
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Vector database objects
- Create and manage vector database instances within the DataRobot Generative AI environment.
- Store unstructured text in chunked form together with numerical embeddings.
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Data source integration
- Connect supported data sources through the DataRobot Data Registry.
- Ingest unstructured text from registered data assets into vector databases.
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Embeddings configuration
- Configure which embedding model or embedding settings are used for stored documents.
- Generate and persist embeddings tied to chunked text for downstream retrieval.
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Chunking configuration
- Define how source documents are split into chunks (for example, by size or structure) before embedding.
- Optimize chunking strategies for retrieval quality and RAG performance.
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RAG integration with LLMs
- Attach vector databases to LLM blueprints in the DataRobot playground.
- Use stored embeddings and chunked content to ground LLM responses in enterprise data.
- Support retrieval-augmented generation workflows directly inside the GenAI platform.
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Playground / blueprint workflow
- Use vector databases as configurable components in LLM blueprints.
- Experiment with different retrieval and grounding setups in the playground environment.
Pricing
- Described as a premium capability of the DataRobot Generative AI platform.
- No specific plans, tiers, or prices are provided in the available content.
Metadata
- Slug:
datarobot-vector-databases-genai - Category:
managed-vector-databases - Tags:
rag,vector-store,enterprise - Brand logo: https://www.datarobot.com/wp-content/uploads/2023/09/datarobot-logo.svg
- Images:
- https://www.datarobot.com/wp-content/uploads/2023/09/product-genai-waterfall-1.png
- https://www.datarobot.com/wp-content/uploads/2023/09/product-genai-waterfall-2.png
- Source URL: https://community.datarobot.com/t5/product-support/set-optional-feature-on-prediction-through-api/m-p/15168
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