Favorite Panasonic Avionics Corporation provides in-flight entertainment and connectivity (IFEC) systems across a large global fleet serving hundreds of airlines and billions of passengers annually. When a system issue affects passenger experience at this scale, engineers must diagnose the root cause quickly across thousands of unique deployment configurations. Doing this
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Shared by AWS Machine Learning August 22, 2026
Favorite Input tokens sent to the foundation model (FM) on every call are often a meaningful part of the cost of running Retrieval Augmented Generation (RAG) at scale. Query-aware compression offers one way to reduce how many of them reach the model. Amazon Bedrock provides the foundation models and features
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Shared by AWS Machine Learning August 22, 2026
Favorite In our conversations with customers over the past months, one pattern keeps recurring. Whether they work with coding agents, autonomous agents, or human-interactive ones, and regardless of workload maturity, we start with the same question: “Which AI agents have access to customer data, who granted it, and what would
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Shared by AWS Machine Learning August 22, 2026
Favorite Data engineering teams routinely spend weeks standing up a single new data source: writing ETL, hand-writing quality checks, updating semantic models, and validating compliance. The Agentic Data Operations Platform (ADOP) on AWS is designed to significantly accelerate that timeline. It’s a reference architecture built on Amazon Bedrock and your
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Shared by AWS Machine Learning August 22, 2026
Favorite KnowledgeForge is about mining gold from the IT Service Management (ITSM) ticket graveyard: the resolved incident tickets whose knowledge never reaches a knowledge base article. Enterprise IT support teams resolve thousands of tickets every month, and each one holds something useful: a symptom, a root cause, and the fix
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Shared by AWS Machine Learning August 21, 2026
Favorite Fanatics Betting and Gaming (FBG) built a multi-agent customer support system on AWS to solve a challenge unique to sports betting. Customers expect instant, accurate answers, especially during live events when every minute counts. Customers ask about account issues, deposit limits, state-specific regulations, and responsible gaming resources. The rules
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Shared by AWS Machine Learning August 21, 2026
Favorite Asynchronous invocation patterns for Amazon Bedrock AgentCore agents in serverless pipelines remove idle compute costs while your AI agent processes requests. A common example is document validation: in a real-estate financing back office, an agent can read a property record or loan contract, reason about whether the information is
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Shared by AWS Machine Learning August 21, 2026
Favorite Mortgage lending runs on documents. Every loan starts with a familiar set: earnings statements, W-2s, bank statements, driver’s licenses, voided checks, and insurance applications. Every lender processes them at scale. The challenge of classifying, extracting, and validating high volumes of documents isn’t unique to mortgage lending. Organizations in banking,
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Shared by AWS Machine Learning August 21, 2026
Favorite If you manage Fast Healthcare Interoperability Resources (FHIR) APIs, you must balance open patient data access with strict data protection requirements. Static security rules require constant updates as clinical workflows evolve, and maintaining them manually creates compliance gaps. With Amazon Bedrock, a fully managed service that provides access to
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Shared by AWS Machine Learning August 21, 2026
Favorite Agentic AI is changing how you work, and vector search powers the retrieval layer that makes agents accurate, contextual, and grounded in real data. Agents plan, reason, and take action across multi-step workflows, making fast, relevant access to your organization’s knowledge essential. That knowledge already has a home across
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Shared by AWS Machine Learning August 21, 2026
Shared by AWS Machine Learning August 22, 2026
