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Practical writing on software architecture, SaaS products, AI automation, legacy modernisation, and the business of building reliable systems.

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Curated links from external sources — not 360Softy original articles.

ExternalAI
AWS Machine Learning Blog

How AWS SMGS uses an AI-powered conversational assistant to transform business management with Amazon Bedrock AgentCore

In this post, we share how we built NarrateAI using Amazon Bedrock AgentCore to deliver business intelligence at scale for the AWS SMGS (Sales, Marketing and Global Services) organization. You will learn about: the two-layer architecture that separates batch processing from real-time interaction, the specialized AI agents that power intelligent routing and validation, key engineering patterns for production deployment, and how to build similar solutions with AWS services.

Amazon Bedrock AgentCoreAmazon Quick SuiteTechnical How-to
AWS Machine Learning BlogRead original
ExternalDatabase
AWS Database Blog

Real-time personalized recommendations with Amazon SageMaker and Amazon-managed Valkey

Amazon receives millions of visits every day, and earning each customer’s trust visit after visit is the foundation that the store is built on. A meaningful part of that trust comes down to whether the recommendations we surface feel relevant and whether they reflect what the customer actually cares about in the moment. In this post, we describe an architecture that makes it achievable. Amazon SageMaker hosts a sentence transformer model on a managed endpoint and turns customer query text into d

Advanced (300)Amazon ElastiCacheAmazon MemoryDB
AWS Database BlogRead original
ExternalDatabase
AWS Database Blog

Optimize costs in Amazon Aurora

By implementing modern optimization techniques for Aurora, you can achieve additional cost reduction beyond traditional methods alone. This isn’t only about spending less—it’s about building a more efficient, scalable, and resilient database environment. In this post, we show you a structured approach to optimizing Amazon Aurora database costs. It outlines specific strategies, implementation steps, and best practices across different optimization areas.

Advanced (300)Amazon AuroraBest Practices
AWS Database BlogRead original
ExternalAI
AWS Machine Learning Blog

Powering agentic AI sales strategy with Amazon Bedrock AgentCore

As agent adoption scaled, we saw a common pattern emerge across enterprises, including our own sales organization: specialized agents deliver value, but without orchestration, users carry the cognitive load of choosing between them. At AWS Sales, this meant more than 20 domain-specific agents deployed across the global organization, with representatives context-switching between systems instead of […]

Amazon BedrockAmazon Bedrock AgentCoreCustomer Solutions
AWS Machine Learning BlogRead original
ExternalSoftware Engineering
DZone

Stop Running Two Data Systems for One Agent Query

If you've deployed a retrieval-augmented generation (RAG) pipeline over enterprise data, you've probably ended up in the same place: Pinecone or Weaviate for embeddings, Delta Lake or Iceberg for structured data, and some custom middleware stitching them together that nobody fully owns. This split made sense historically. Vector databases existed before lakehouse formats efficiently supported high-dimensional arrays. Standing up a Pinecone index was faster than waiting for your data platform to

DZoneRead original

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