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Conventional RAG Falls Short with Enterprise Databases

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    * [![vid-icon](https://www.gigaspaces.com/wp-content/uploads/2024/07/solutons.png) Massimo Pezzini, Gartner Analyst Emeritus  ](https://go.gigaspaces.com/5-top-use-cases-for-driving-business-with-data-hub-architecture)

5 Top Use Cases For Driving Business With Data Hub Architecture 

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      * [Asked & Answered in Natural Language](https://www.gigaspaces.com/how-it-works/asked-answered-natural-language)
      * [Multiple Data Sources](https://www.gigaspaces.com/how-it-works/supported-data-sources)
      * [Proactive AI Governance](https://www.gigaspaces.com/how-it-works/proactive-ai-governance)
    * [![vid-icon](https://www.gigaspaces.com/wp-content/uploads/2025/02/How-it-works-menu.jpg)](https://go.gigaspaces.com/effective-ai-governance-wp)

Ensure GenAI compliance and governance 

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      * [Budget Management](https://www.gigaspaces.com/use-cases/educational-organizations-budget-resources)
      * [Sales Operations](https://www.gigaspaces.com/use-cases/retail-boost-sales)
      * [Service Providers](https://www.gigaspaces.com/use-cases/contract-control-cost-savings)
      * [Utilities Management](https://www.gigaspaces.com/use-cases/cut-sla-penalties)
      * [Restaurant Management](https://www.gigaspaces.com/use-cases/power-smarter-restaurant-growth-erag)
    * By Industry

      * [Logistics](https://www.gigaspaces.com/case-studies/optimizing-supply-chain-with-ai-powered-insights)
      * [Pharma](https://www.gigaspaces.com/case-studies/transforming-patient-outcomes)
      * [Education](https://www.gigaspaces.com/case-studies/achieving-educational-budget-control)
      * [Retail](https://www.gigaspaces.com/case-studies/retail-intelligence-with-erag)
      * [Shipping](https://www.gigaspaces.com/case-studies/redefining-global-logistics)
      * [Energy](https://www.gigaspaces.com/case-studies/boosting-operations-reducing-penalties)
      * [Hospitality](https://www.gigaspaces.com/case-studies/restaurant-increase-profit-erag)
    * [![vid-icon](https://www.gigaspaces.com/wp-content/uploads/2025/02/Company-menu-thumb.jpg)](https://go.gigaspaces.com/webinarod/ecurely-unlocking-structured-data-for-enterprise-ai-0)

Monkey See, AI Do - All about CUA

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    * [![vid-icon](https://www.gigaspaces.com/wp-content/uploads/2025/02/Resources-menu-thumb.jpg)](https://www.gigaspaces.com/blog/from-rag-to-tag)

Taking the AI leap from RAG to TAG

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GigaSpaces, IBM & AWS make AI safer

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    * Our Products

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        * [GenAI Catalyst](https://www.gigaspaces.com/products/genai-catalyst)
        * [Instant Data](https://www.gigaspaces.com/products/instant-data)
        * [Respond Proactively](https://www.gigaspaces.com/products/proactive-ai)
        * [Act Autonomously](https://www.gigaspaces.com/products/data-autonomy)
      * [Smart DIH](https://www.gigaspaces.com/products/smart-digital-integration-hub-lobby)
      * [XAP](https://www.gigaspaces.com/products/xap-imdg)
    * Solutions for

      * [Pharma](https://www.gigaspaces.com/products/erag/pharma)
      * [Procurement](https://www.gigaspaces.com/products/erag/procurement)
    * [![vid-icon](https://www.gigaspaces.com/wp-content/uploads/2025/02/Product-menu-thumb.jpg)](https://go.gigaspaces.com/webinar/why-conventional-rag-falls-short)

Conventional RAG Falls Short with Enterprise Databases

[Watch the Webinar![icon](/wp-content/uploads/2023/04/Group-30743.png)](https://go.gigaspaces.com/webinar/why-conventional-rag-falls-short)

  * Solutions![](https://www.gigaspaces.com/wp-content/uploads/2022/11/Path-16484.svg)

    * Business Solutions

      * [Digital Innovation Over Legacy Systems](https://www.gigaspaces.com/use-cases/digital-innovation-acceleration)
      * [Integration Data Hub](https://www.gigaspaces.com/technology/integration-data-hub)
      * [API Scaling](https://www.gigaspaces.com/use-cases/application-acceleration)
      * [Hybrid / Multi-cloud Integration](https://www.gigaspaces.com/use-cases/hybrid-or-multi-cloud-integration)
      * [Customer 360](https://www.gigaspaces.com/use-cases/customer-360)
      * Industry Solutions
      * [Retail](https://www.gigaspaces.com/retail-and-ecommerce-2)
      * [Financial Services](https://www.gigaspaces.com/financial-services)
      * [Insurance Companies](https://www.gigaspaces.com/industry-solutions/insurance)
    * [![vid-icon](https://www.gigaspaces.com/wp-content/uploads/2024/07/solutons.png) Massimo Pezzini, Gartner Analyst Emeritus  ](https://go.gigaspaces.com/5-top-use-cases-for-driving-business-with-data-hub-architecture)

5 Top Use Cases For Driving Business With Data Hub Architecture 

[Watch the Webinar![icon](/wp-content/uploads/2023/04/Group-30743.png)](https://go.gigaspaces.com/5-top-use-cases-for-driving-business-with-data-hub-architecture)

  * How it Works![](https://www.gigaspaces.com/wp-content/uploads/2022/11/Path-16484.svg)

    * [eRAG Technology Overview](/how-it-works/erag-how-it-works)

      * [AI-Ready, IT-Friendly](https://www.gigaspaces.com/products/ai-ready)
      * [Semantic Reasoning](https://www.gigaspaces.com/how-it-works/semantic-reasoning)
      * [Questions to SQL Queries](https://www.gigaspaces.com/how-it-works/questions-into-sql-queries)
      * [Asked & Answered in Natural Language](https://www.gigaspaces.com/how-it-works/asked-answered-natural-language)
      * [Multiple Data Sources](https://www.gigaspaces.com/how-it-works/supported-data-sources)
      * [Proactive AI Governance](https://www.gigaspaces.com/how-it-works/proactive-ai-governance)
    * [![vid-icon](https://www.gigaspaces.com/wp-content/uploads/2025/02/How-it-works-menu.jpg)](https://go.gigaspaces.com/effective-ai-governance-wp)

Ensure GenAI compliance and governance 

[Read the Whitepaper![icon](/wp-content/uploads/2023/04/Group-30743.png)](https://go.gigaspaces.com/effective-ai-governance-wp)

  * [Success Stories![](https://www.gigaspaces.com/wp-content/uploads/2022/11/Path-16484.svg)](https://www.gigaspaces.com/case-studies)

    * By Use Case

      * [Procurement](https://www.gigaspaces.com/use-cases/procurement-supply-chain)
      * [Operations](https://www.gigaspaces.com/use-cases/enhancing-pharmaceutical-operations)
      * [Budget Management](https://www.gigaspaces.com/use-cases/educational-organizations-budget-resources)
      * [Sales Operations](https://www.gigaspaces.com/use-cases/retail-boost-sales)
      * [Service Providers](https://www.gigaspaces.com/use-cases/contract-control-cost-savings)
      * [Utilities Management](https://www.gigaspaces.com/use-cases/cut-sla-penalties)
      * [Restaurant Management](https://www.gigaspaces.com/use-cases/power-smarter-restaurant-growth-erag)
    * By Industry

      * [Logistics](https://www.gigaspaces.com/case-studies/optimizing-supply-chain-with-ai-powered-insights)
      * [Pharma](https://www.gigaspaces.com/case-studies/transforming-patient-outcomes)
      * [Education](https://www.gigaspaces.com/case-studies/achieving-educational-budget-control)
      * [Retail](https://www.gigaspaces.com/case-studies/retail-intelligence-with-erag)
      * [Shipping](https://www.gigaspaces.com/case-studies/redefining-global-logistics)
      * [Energy](https://www.gigaspaces.com/case-studies/boosting-operations-reducing-penalties)
      * [Hospitality](https://www.gigaspaces.com/case-studies/restaurant-increase-profit-erag)
    * [![vid-icon](https://www.gigaspaces.com/wp-content/uploads/2025/02/Company-menu-thumb.jpg)](https://go.gigaspaces.com/webinarod/ecurely-unlocking-structured-data-for-enterprise-ai-0)

Monkey See, AI Do - All about CUA

[Watch Webinar![icon](/wp-content/uploads/2023/04/Group-30743.png)](https://go.gigaspaces.com/webinarod/ecurely-unlocking-structured-data-for-enterprise-ai-0)

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    * [![vid-icon](https://www.gigaspaces.com/wp-content/uploads/2025/02/Resources-menu-thumb.jpg)](https://www.gigaspaces.com/blog/from-rag-to-tag)

Taking the AI leap from RAG to TAG

[Read the Blog![icon](/wp-content/uploads/2023/04/Group-30743.png)](https://www.gigaspaces.com/blog/from-rag-to-tag)

  * Company![](https://www.gigaspaces.com/wp-content/uploads/2022/11/Path-16484.svg)

    * Our Company

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      * [Customers](https://www.gigaspaces.com/customers)
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    * col2

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      * [System Integrators](https://www.gigaspaces.com/partners-lobby/system-integrators)
      * [Technology Partners](https://www.gigaspaces.com/partners-lobby/technology)
      * [Value Added Resellers](https://www.gigaspaces.com/partners-lobby/value-added-resellers)
      * Support & Services
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      * [Support](https://www.gigaspaces.com/support-lobby)
    * [![vid-icon](https://www.gigaspaces.com/wp-content/uploads/2025/02/Company-menu-thumb.jpg)](https://www.gigaspaces.com/news/gigaspaces-partners-with-ibm-and-aws-to-deliver-accurate-safe-genai-with-dbs)

GigaSpaces, IBM & AWS make AI safer

[Read How![icon](/wp-content/uploads/2023/04/Group-30743.png)](https://www.gigaspaces.com/news/gigaspaces-partners-with-ibm-and-aws-to-deliver-accurate-safe-genai-with-dbs)

  * [Book a Demo](https://www.gigaspaces.com/book-a-demo)



  * Products
    * Our Products
      * [eRAG](https://www.gigaspaces.com/products/erag)
        * [GenAI Catalyst](https://www.gigaspaces.com/products/genai-catalyst)
        * [Instant Data](https://www.gigaspaces.com/products/instant-data)
        * [Respond Proactively](https://www.gigaspaces.com/products/proactive-ai)
        * [Act Autonomously](https://www.gigaspaces.com/products/data-autonomy)
      * [Smart DIH](https://www.gigaspaces.com/products/smart-digital-integration-hub)
      * [XAP](https://www.gigaspaces.com/products/xap-imdg)
    * Solutions for
      * [Pharma](https://www.gigaspaces.com/products/erag/pharma)
      * [Procurement](https://www.gigaspaces.com/products/erag/procurement)
  * Solutions
    * [Digital Innovation Over Legacy Systems](https://www.gigaspaces.com/use-cases/digital-innovation-acceleration)
    * [Integration Data Hub](https://www.gigaspaces.com/technology/integration-data-hub)
    * [API Scaling](https://www.gigaspaces.com/use-cases/application-acceleration)
    * [Hybrid/Multi-cloud Integration](https://www.gigaspaces.com/use-cases/hybrid-or-multi-cloud-integration)
    * [Customer 360](https://www.gigaspaces.com/use-cases/customer-360)
    * [Retail](https://www.gigaspaces.com/retail-and-ecommerce-2)
    * [Financial Services](https://www.gigaspaces.com/financial-services)
    * [Insurance Companies](https://www.gigaspaces.com/industry-solutions/insurance)
  * How it Works
    * [eRAG Technology Overview](https://www.gigaspaces.com/how-it-works/erag-how-it-works)
      * [AI-Ready, IT-Friendly](https://www.gigaspaces.com/products/ai-ready)
      * [Semantic Reasoning](https://www.gigaspaces.com/how-it-works/semantic-reasoning)
      * [Questions to SQL Queries](https://www.gigaspaces.com/how-it-works/questions-into-sql-queries)
      * [Asked & Answered in Natural Language](https://www.gigaspaces.com/how-it-works/asked-answered-natural-language)
      * [Multiple Data Sources](https://www.gigaspaces.com/how-it-works/supported-data-sources)
      * [Governance](https://www.gigaspaces.com/how-it-works/proactive-ai-governance)
  * [Success Stories](https://www.gigaspaces.com/case-studies)
    * By Use Case
      * [Procurement](https://www.gigaspaces.com/use-cases/procurement-supply-chain)
      * [Operations](https://www.gigaspaces.com/use-cases/enhancing-pharmaceutical-operations)
      * [Budget Management](https://www.gigaspaces.com/use-cases/educational-organizations-budget-resources)
      * [Sales Operations](https://www.gigaspaces.com/use-cases/retail-boost-sales)
      * [Service Providers](https://www.gigaspaces.com/use-cases/contract-control-cost-savings)
      * [Utilities Management](https://www.gigaspaces.com/use-cases/cut-sla-penalties)
      * [Restaurant Management](https://www.gigaspaces.com/use-cases/power-smarter-restaurant-growth-erag)
    * By Industry
      * [Logistics](https://www.gigaspaces.com/case-studies/optimizing-supply-chain-with-ai-powered-insights)
      * [Pharma](https://www.gigaspaces.com/case-studies/transforming-patient-outcomes)
      * [Education](https://www.gigaspaces.com/case-studies/achieving-educational-budget-control)
      * [Retail](https://www.gigaspaces.com/case-studies/retail-intelligence-with-erag)
      * [Shipping](https://www.gigaspaces.com/case-studies/redefining-global-logistics)
      * [Energy](https://www.gigaspaces.com/case-studies/boosting-operations-reducing-penalties)
      * [Hospitality](https://www.gigaspaces.com/case-studies/restaurant-increase-profit-erag)
  * Resources
    * [Webinars](https://www.gigaspaces.com/resources/webinars)
    * [Videos](https://www.gigaspaces.com/resources/videos)
    * [Q&As](https://www.gigaspaces.com/answers)
    * [Whitepapers & Brochures](https://www.gigaspaces.com/resources/brochures)
    * [Customer Case Studies](https://www.gigaspaces.com/resources/case-studies)
    * [Events](https://www.gigaspaces.com/resources/events/)
    * [Glossary](https://www.gigaspaces.com/data-terms)
    * [FAQs](https://www.gigaspaces.com/products/erag/faq)
    * [Blog](https://www.gigaspaces.com/blog)
    * [Technical Documentation](https://docs.www.gigaspaces.com/latest/landing.html)
  * Company
    * [About](https://www.gigaspaces.com/about)
    * [Customers](https://www.gigaspaces.com/customers)
    * [Management](https://www.gigaspaces.com/leadership)
    * [Board Members](https://www.gigaspaces.com/board-members)
    * [Investors](https://www.gigaspaces.com/investors)
    * [News](https://www.gigaspaces.com/news)
    * [Press Releases](https://www.gigaspaces.com/press-releases)
    * [Careers](https://www.gigaspaces.com/career-lobby)
    * [Partners](https://www.gigaspaces.com/partners-lobby)
      * [OEM Partners](https://www.gigaspaces.com/partners-lobby/oem)
      * [System Integrators](https://www.gigaspaces.com/partners-lobby/system-integrators)
      * [Technology Partners](https://www.gigaspaces.com/partners-lobby/technology)
      * [Value Added Resellers](https://www.gigaspaces.com/partners-lobby/value-added-resellers)
    * Support & Services
      * [Services](https://www.gigaspaces.com/service-overview)
      * [Support](https://www.gigaspaces.com/support-lobby)
  * [Pricing](https://www.gigaspaces.com/pricing)
  * [Book a Demo](https://www.gigaspaces.com/?schedule-meeting-form=true)



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# Cache Augmented Generation (CAG)

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## What is Cache Augmented Generation?

Cache Augmented Generation (CAG) is a method designed to boost the performance of AI systems, particularly those that use [Retrieval-Augmented Generation](https://www.gigaspaces.com/data-terms/retrieval-augmented-generation) (RAG) frameworks such as RAG LangChain (LangChain is a tool that helps developers build agents that can think through problems and break them into smaller steps.)

By combining caching with AI-generated responses, CAG helps AI systems become faster and more efficient. When AI models need to access external knowledge — like databases, vector stores, or search engines — CAG allows them to check a cache first, and, if the answer is already stored, the system can provide it immediately, which saves time and computational resources.

In essence, CAG adds a caching layer to the knowledge retrieval process, which enables systems to reuse [previously retrieved data](https://www.gigaspaces.com/data-terms/caching-as-a-service) instead of having to run costly and repetitive searches.

## How Cache Augmented Generation Works

Examining a typical [AI pipeline](https://www.gigaspaces.com/blog/creating-data-pipelines) that uses RAG LangChain makes it clearer how cache augmented generation knowledge retrieval works. Normally, when a user query is entered into an AI model, the model searches an external source of knowledge (such as a vector database) to find any documents or data that are relevant. These results are then used to generate a final answer or response.

However, [CAG ](https://www.gigaspaces.com/blog/cag-tag-multi-agentic-rag)optimizes this process. It works as follows: 

**User Query:** The user sends a question to the AI system.

**Cache Check:** Before querying external sources, the system [checks an in-memory cache](https://www.gigaspaces.com/blog/in-memory-cache/) to see if a similar or identical question has already been answered.

**Cache Hit or Miss:**

If found (cache hit), then the system retrieves the cached data and uses it to generate an answer at once.

If not found (cache miss), the system will then retrieve data from the external source as usual.

**Cache Update:** After retrieving and using external data, the system stores the result in the cache for future use.

**Answer Generation:** The AI model uses the retrieved (or cached) data to generate a final response to the user.

In this way, cache augmented generation makes knowledge retrieval more simple by cutting redundant queries and limiting latency.

## The Key Components of CAG

There are several key components that make cache augmented generation work effectively:

  * **In-Memory Cache** : This is the heart of CAG. It stores recently retrieved documents, responses, or embeddings in memory for quick and easy access. A slew of tools like Redis, Memcached, or in-process caches can be used depending on the scale of the system.
  * **Similarity Search Function** : Not all user queries will be the same, so CAG often uses semantic similarity search (such as using embeddings) to check if there are already similar queries in the cache.
  * **Retrieval System (RAG Pipeline)** : If the system finds no cached result, it falls back on standard RAG LangChain processes to query databases, vector stores, or APIs to gather knowledge.
  * **Cache Management Logic** : This handles cache expiration, size limits, and updates so that the cache remains relevant and doesn’t grow indefinitely.
  * **AI Generation Module** : Once data is retrieved (from cache or source), a language model (like GPT-4 or similar) uses it to generate a response.



## The Benefits of Cache Augmentation in AI Models

Adding caching to AI-driven knowledge retrieval pipelines like RAG brings several significant benefits:

  * **Less Latency** : Since data is served directly from the cache when possible, response times are much faster — often near real-time.
  * **Lower Costs** : Querying external knowledge bases (like databases or APIs) can be costly in terms of both compute and API fees. By reusing cached data, CAG reduces the frequency of these calls.
  * **Better Scalability** : CAG lets AI systems handle more users at once without overloading backend systems.
  * **More consistency** : Frequently asked questions (FAQs) or common queries return consistent results when served from the cache, improving the user experience.
  * **Boosted resilience** : If external sources are temporarily unavailable, cached responses can still provide service continuity.



## How CAG Improves Language Model Outputs

Although the main focus of cache augmented generation is efficiency, it has the added benefit of enhancing both the quality and consistency of AI-generated outputs. 

It does this in several ways. For one, rapidly retrieving the relevant data enables language models to generate informed and accurate answers with very little delay. Also, because CAG can store high-quality, curated responses, subsequent users benefit from information that becomes more polished and precise over time.

In conversational AI, CAG can cache parts of ongoing discussions, which helps maintain context over multiple turns without the need for repeated retrieval. Finally, systems can analyze which cached responses are used the most and prioritize updating or improving those responses, which helps the AI grow smarter over time.

In your usual RAG LangChain setup, generating a response is often an onerous process, with complex retrieval and reasoning steps. However, integrating CAG helps skip many of these steps for known queries, considerably improving the overall experience for developers and users alike.

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