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Extending public sector intelligence with Agentforce and AWS

Favorite Public sector agencies process large volumes of unstructured evidence, such as body camera footage, surveillance video, and scanned documents, that require extracting insights before anyone can act on them. This post shows how to combine Amazon Bedrock Data Automation with the Model Context Protocol (MCP) to turn unstructured data

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Shared by AWS Machine Learning September 22, 2026

How Trane gets building insights 60x faster with Amazon Bedrock AgentCore

Favorite Trane Technologies manages millions of connected heating, ventilation, and air conditioning (HVAC) assets worldwide, but getting a single operational answer could mean cross-referencing multiple dashboards and drilling through menus for 20 minutes or more. For organizations operating at this scale, that kind of friction slows operations, defers corrective action,

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Shared by AWS Machine Learning September 22, 2026

Right-size generative AI endpoints with concurrency sweeps on Amazon SageMaker AI

Favorite Concurrency sweeps help you right-size a generative AI endpoint by finding the instance type and serving configuration that maximizes price-performance while holding latency within acceptable bounds. Without a systematic approach, right-sizing means deploying, load-testing manually, adjusting, and repeating until the numbers look acceptable. Choose five ml.g7e.2xlarge instances when one

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Shared by AWS Machine Learning September 22, 2026

Migrating multi-model AI agents to Amazon Bedrock AgentCore runtime

Favorite Organizations building multi-model agentic AI applications face growing infrastructure complexity. Managing container orchestration, scaling policies, identity, and observability for multiple model types adds operational overhead. Teams often spend more time on infrastructure than on agent logic development. Developers running agentic frameworks on self-managed infrastructure such as Amazon Elastic Container

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Shared by AWS Machine Learning September 19, 2026

Introducing Kimi K3 on Amazon Bedrock

Favorite Open-weight models are changing the economics of building and deploying AI at scale. Rapid gains in intelligence and efficiency mean companies can match each workload with the right balance of capability, speed, and cost. AWS is building for a future in which organizations can adopt open-weight innovation with the

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Shared by AWS Machine Learning September 19, 2026