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Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

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Recent advances in generative AI have led to the rapid evolution of natural language to SQL (NL2SQL) technology, which uses pre-trained large language models (LLMs) and natural language to generate database queries in the moment.

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From Chaos to Control: A Cost Maturity Journey with Databricks

databricks

Classic compute (workflows, Declarative Pipelines, SQL Warehouse, etc.) inherits tags on the cluster definition, while serverless adheres to Serverless Budget Policies ( AWS | Azure | GCP ). In general, you can add tags to two kinds of resources: Compute Resources: Includes SQL Warehouse, jobs, instance pools, etc.

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AWS doubles investment in AWS Generative AI Innovation Center, marking two years of customer success

AWS Machine Learning Blog

When we launched the AWS Generative AI Innovation Center in 2023, we had one clear goal: help customers turn AI potential into real business value. Proven results through collaborative innovation The AWS Generative AI Innovation Center delivers results by empowering customers to innovate freely and maximize value through trusted AI solutions.

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How AWS sales uses Amazon Q Business for customer engagement

AWS Machine Learning Blog

Earlier this year, we published the first in a series of posts about how AWS is transforming our seller and customer journeys using generative AI. Field Advisor serves four primary use cases: AWS-specific knowledge search With Amazon Q Business, weve made internal data sources as well as public AWS content available in Field Advisors index.

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Build a conversational data assistant, Part 1: Text-to-SQL with Amazon Bedrock Agents

AWS Machine Learning Blog

For most organizations, this gap remains stubbornly wide, with business teams trapped in endless cycles—decoding metric definitions and hunting for the correct data sources to manually craft each SQL query. In Part 1, we focus on building a Text-to-SQL solution with Amazon Bedrock , a managed service for building generative AI applications.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning Blog

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. You can use AWS services such as Application Load Balancer to implement this approach. On AWS, you can use the fully managed Amazon Bedrock Agents or tools of your choice such as LangChain agents or LlamaIndex agents.

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AWS at Databricks Data + AI Summit 2025

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AWS’ Legendary Presence at DAIS: Customer Speakers, Featured Breakouts, and Live Demos! Amazon Web Services (AWS) returns as a Legend Sponsor at Data + AI Summit 2025 , the premier global event for data, analytics, and AI.

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