Remove Data Ingestion Remove Information Remove Metadata
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Multi-tenancy in RAG applications in a single Amazon Bedrock knowledge base with metadata filtering

AWS Machine Learning Blog

Amazon Bedrock Knowledge Bases offers fully managed, end-to-end Retrieval Augmented Generation (RAG) workflows to create highly accurate, low-latency, secure, and custom generative AI applications by incorporating contextual information from your companys data sources.

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The importance of data ingestion and integration for enterprise AI

IBM Journey to AI blog

In the generative AI or traditional AI development cycle, data ingestion serves as the entry point. Here, raw data that is tailored to a company’s requirements can be gathered, preprocessed, masked and transformed into a format suitable for LLMs or other models. One potential solution is to use remote runtime options like.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

Flipboard

Amazon Q Business , a new generative AI-powered assistant, can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in an enterprises systems. Large-scale data ingestion is crucial for applications such as document analysis, summarization, research, and knowledge management.

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Secure a generative AI assistant with OWASP Top 10 mitigation

Flipboard

This comprehensive security setup addresses LLM10:2025 Unbound Consumption and LLM02:2025 Sensitive Information Disclosure, making sure that applications remain both resilient and secure. In the physical architecture diagram, the application controller is the LLM orchestrator AWS Lambda function.

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How AWS Sales uses generative AI to streamline account planning

AWS Machine Learning Blog

Data synthesis: The assistant can pull relevant information from multiple sources including from our customer relationship management (CRM) system, financial reports, news articles, and previous APs to provide a holistic view of our customers.

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LlamaIndex: Augment your LLM Applications with Custom Data Easily

Unite.AI

There is also the challenge of privacy and data security, as the information provided in the prompt could potentially be sensitive or confidential. On the other hand, a Node is a snippet or “chunk” from a Document, enriched with metadata and relationships to other nodes, ensuring a robust foundation for precise data retrieval later on.

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How Deltek uses Amazon Bedrock for question and answering on government solicitation documents

AWS Machine Learning Blog

Deltek serves over 30,000 clients with industry-specific software and information solutions. Deltek is continuously working on enhancing this solution to better align it with their specific requirements, such as supporting file formats beyond PDF and implementing more cost-effective approaches for their data ingestion pipeline.