Technical How-to

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How Gardenia Technologies helps customers create ESG disclosure reports 75% faster using agentic generative AI on Amazon Bedrock

Advanced (300), Amazon Bedrock, Amazon Bedrock Agents, Amazon Textract, Customer Solutions, Intermediate (200), Sustainability, Technical How-to /

This post was co-written with Federico Thibaud, Neil Holloway, Fraser Price, Christian Dunn, and Frederica Schrager from Gardenia Technologies “What gets measured gets managed” has become a guiding principle for organizations worldwide as they begin their sustainability and environmental, social, and governance (ESG) journeys. Companies are establishing baselines to track their progress, supported by an expanding framework of reporting standards, […]

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Automate customer support with Amazon Bedrock, LangGraph, and Mistral models

Amazon Bedrock, Amazon Bedrock Guardrails, Generative AI, Intermediate (200), Technical How-to /

AI agents are transforming the landscape of customer support by bridging the gap between large language models (LLMs) and real-world applications. These intelligent, autonomous systems are poised to revolutionize customer service across industries, ushering in a new era of human-AI collaboration and problem-solving. By harnessing the power of LLMs and integrating them with specialized tools

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Build responsible AI applications with Amazon Bedrock Guardrails

Amazon Bedrock, Amazon Bedrock Guardrails, Generative AI, Intermediate (200), Technical How-to /

As organizations embrace generative AI, they face critical challenges in making sure their applications align with their designed safeguards. Although foundation models (FMs) offer powerful capabilities, they can also introduce unique risks, such as generating harmful content, exposing sensitive information, being vulnerable to prompt injection attacks, and returning model hallucinations. Amazon Bedrock Guardrails has helped

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Stream multi-channel audio to Amazon Transcribe using the Web Audio API

AI/ML, Amazon Transcribe, Technical How-to /

Multi-channel transcription streaming is a feature of Amazon Transcribe that can be used in many cases with a web browser. Creating this stream source has it challenges, but with the JavaScript Web Audio API, you can connect and combine different audio sources like videos, audio files, or hardware like microphones to obtain transcripts. In this

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Build a serverless audio summarization solution with Amazon Bedrock and Whisper

Amazon API Gateway, Amazon Bedrock, Amazon Bedrock Guardrails, Amazon EventBridge, Application Integration, Architecture, AWS Step Functions, Best Practices, Generative AI, Technical How-to /

Recordings of business meetings, interviews, and customer interactions have become essential for preserving important information. However, transcribing and summarizing these recordings manually is often time-consuming and labor-intensive. With the progress in generative AI and automatic speech recognition (ASR), automated solutions have emerged to make this process faster and more efficient. Protecting personally identifiable information (PII)

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Implement semantic video search using open source large vision models on Amazon SageMaker and Amazon OpenSearch Serverless

Amazon Machine Learning, Amazon OpenSearch Service, Amazon SageMaker, Amazon SageMaker AI, Best Practices, Generative AI, Technical How-to, Video analysis /

As companies and individual users deal with constantly growing amounts of video content, the ability to perform low-effort search to retrieve videos or video segments using natural language becomes increasingly valuable. Semantic video search offers a powerful solution to this problem, so users can search for relevant video content based on textual queries or descriptions.

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Build a Text-to-SQL solution for data consistency in generative AI using Amazon Nova

Amazon Bedrock, Amazon Nova, Customer Solutions, Technical How-to /

Businesses rely on precise, real-time insights to make critical decisions. However, enabling non-technical users to access proprietary or organizational data without technical expertise remains a challenge. Text-to-SQL bridges this gap by generating precise, schema-specific queries that empower faster decision-making and foster a data-driven culture. The problem lies in obtaining deterministic answers—precise, consistent results needed for

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Supercharge your development with Claude Code and Amazon Bedrock prompt caching

Amazon Bedrock, Artificial Intelligence, Foundation models, Generative AI, Technical How-to /

Prompt caching in Amazon Bedrock is now generally available, delivering performance and cost benefits for agentic AI applications. Coding assistants that process large codebases represent an ideal use case for prompt caching. In this post, we’ll explore how to combine Amazon Bedrock prompt caching with Claude Code—a coding agent released by Anthropic that is now

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Unlocking the power of Model Context Protocol (MCP) on AWS

Foundation models, Generative AI, Intermediate (200), Technical How-to /

We’ve witnessed remarkable advances in model capabilities as generative AI companies have invested in developing their offerings. Language models such as Anthropic’s Claude Opus 4 & Sonnet 4, Amazon Nova, and Amazon Bedrock can reason, write, and generate responses with increasing sophistication. But even as these models grow more powerful, they can only work with

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Build GraphRAG applications using Amazon Bedrock Knowledge Bases

Amazon Bedrock, Amazon Bedrock Knowledge Bases, Amazon Neptune, Amazon Neptune Analytics, Technical How-to /

In these days, it is more common to companies adopting AI-first strategy to stay competitive and more efficient. As generative AI adoption grows, the technology’s ability to solve problems is also improving (an example is the use case to generate comprehensive market report). One way to simplify the growing complexity of problems to be solved

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