NEW! Download Gartner® Report: Use RAG as a Service to Boost Your AI-Ready Data. Get Started.

NEW! Download Gartner® Report: Use RAG as a Service to Boost Your AI-Ready Data. Get Started.

NEW! Download Gartner® Report: Use RAG as a Service to Boost Your AI-Ready Data. Get Started.

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Gartner® Innovation Insight: Use RAG as a Service to Boost Your AI-Ready Data

Gartner® Innovation Insight: Use RAG as a Service to Boost Your AI-Ready Data

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.”

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.”

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.”

understanding the four stages of enterprise search white paper video background image
understanding the four stages of enterprise search white paper video background image
understanding the four stages of enterprise search white paper video background image

The gap between basic RAG implementation and enterprise-grade performance is wider than most organizations realize. According to a latest report by Gartner, while many enterprises successfully deploy basic RAG systems, achieving reliable, high-accuracy results requires mastering multiple customizable components.

The gap between basic RAG implementation and enterprise-grade performance is wider than most organizations realize. According to a latest report by Gartner, while many enterprises successfully deploy basic RAG systems, achieving reliable, high-accuracy results requires mastering multiple customizable components.

Inside the report, you'll discover:

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.

Get Complimentary Access to the Gartner Report

Get Complimentary Access to the Gartner Report

Get Complimentary Access to the Gartner Report

A Transformative Shift with Retrieval Augmented Generation as a Service (RAGaaS)

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."

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

Key Takeaways from the Report

Data Management Platform Integration

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.

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

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.

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 Management

Active metadata offered by many components in RAGaaS is playing an increasingly vital role to ensure transparent and auditable GenAI consumption.

Active metadata offered by many components in RAGaaS is playing an increasingly vital role to ensure transparent and auditable GenAI consumption.

Security and Governance

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.

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

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.

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

Gartner, "Innovation Insight: Use RAG as a Service to Boost Your AI-Ready Data," December 2024

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from SearchBlox

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from SearchBlox

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