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Gartner® Innovation Insight: Use RAG as a Service to Boost Your AI-Ready Data
According to Gartner®, “The popularity of retrieval augmented generation brings organizations a new option to build GenAI-based business applications in a data-centric approach. Data management leaders can use RAG as a service in their data management architecture to provide AI-ready data for business GenAI initiatives.”
Inside the report, you'll discover:
How to evaluate whether your existing organizational data management platform can be enhanced as a RAGaaS platform
Strategies for implementing RAG with seamless integration of vector search, graph, and chunking technologies
Methods for governing GenAI consumption using active metadata and technical controls
Approaches to protect against malicious use, privacy issues, and IP leaking.
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A Transformative Shift with Retrieval Augmented Generation as a Service (RAGaaS)
The integration of retrieval augmented generation in cloud services is transforming how organizations implement GenAI. By 2028, Gartner®, predicts that "80% of business generative AI applications implemented by RAG approach will use organizations' existing data management platforms (including LDW/lakehouse) as the knowledge source, increasing from less than 20% today."
Key Takeaways from the Report
Data Management Platform Integration
RAGaaS combines GenAI application deployment and data management technologies, such as DBMS, metadata management, retrieval engine, embedding, prompt design and LLM APIs into seamlessly integrated services.
Ecosystem Collaboration
Data management technologies to support RAG are rapidly being introduced as new functions on DBMS and data integration solutions, including multimodel data storage, vector/graph/text search, and data ingestion capabilities.
Active Metadata Management
Active metadata offered by many components in RAGaaS is playing an increasingly vital role to ensure transparent and auditable GenAI consumption.
Security and Governance
In-DBMS authorization management ensures that important/privacy data in the organization can only be authorized by entitled users; also serves as the secondary guardrail next to prompt for malicious use of GenAI.
Operational Effectiveness
Compute-storage decoupling has become a standard capability, allowing users to compose different analytic al/retrieval engines including SQL query engines, vector-based retrieval, graph retrieval and keyword retrieval.
Gartner, "Innovation Insight: Use RAG as a Service to Boost Your AI-Ready Data," December 2024
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