Category: Learning Levels

Autonomous AI agents are transforming financial services — but in regulated industries, capability alone doesn’t drive adoption. Trust does. In this post, Fenergo and AWS engineers walk through the architecture behind the Fenergo Agent Operating System (Agent OS): a governance-first layer built on Amazon Bedrock, Amazon DynamoDB, Amazon SNS, Amazon SQS, and Amazon Timestream for InfluxDB that makes every agent decision traceable, explainable, and audit-ready. Learn how to design agentic AI systems that answer the question regulators always ask: why?

A data migration consulting firm’s growth was limited by dependence on a small group of expert practitioners to execute complex validation workflows, creating bottlenecks that delayed client deliverables and constrained profitability. Mission Cloud and AWS built a production AI agent on Amazon Bedrock AgentCore that guides consultants through structured validation workflows and supports natural language SQL analysis, democratizing expertise across the entire team. New employees are onboarded significantly faster, and validation cycles that previously took weeks now complete in days.

F5 AI Guardrails and F5 AI Red Team deliver continuous adaptive security for AI applications on AWS Bedrock. This post introduces three capabilities for enterprise AI security: pre-deployment model evaluation, adversarial testing at scale, and adaptive runtime protection. Learn how these capabilities compress the gap between threat discovery and defense deployment from weeks to minutes.

AWS Partners can now access three new Forward Deployed Engineering (FDE) pathways and earn credentials through AWS Skill Builder to build and validate the depth required for production-ready agentic AI delivery.

The Attributed Revenue Dashboard in AWS Partner Central brings Partner Revenue Measurement insights to life with automated revenue data by Partner product, AWS service, and billing period. Partners can use these insights to demonstrate impact, sharpen co-sell strategies, and unlock greater AWS investment.

The AWS Data Competency (previously AWS Data and Analytics Competency) is expanding with two new categories—Databases and Relational Databases—along with new performance-based Signature benefits for Partners delivering data architectures at scale.

If your RAG deployment has plateaued—struggling with cross-domain reasoning, noisy retrieval at scale, or a model that never truly learns your business—you’re not alone. In this post, we explore how 4MINDS’s continuous model adaptation on AWS moves beyond RAG’s stateless architecture by building enterprise knowledge directly into model parameters, enabling AI that improves with every interaction. Learn how this AWS Marketplace solution integrates with Amazon Bedrock and Amazon SageMaker to deliver domain-adapted models without the operational burden of traditional fine-tuning.

Learn how a major UK energy retailer partnered with Gorilla, an AWS Partner, to transform its residential pricebook process from a 10 to 14 day manual workflow into an automated, cloud-native solution that delivers updated pricing in under one hour, achieving a 95% reduction in cycle time, 75% fewer pricing errors, and full Market-wide Half Hourly Settlement (MHHS) compliance, all without replacing its existing SAP IS-U infrastructure.

Nubank, one of the world’s largest digital banks, runs entirely on AWS while serving 119 million customers. Nubank achieved over $15 million in verified annualized savings by partnering with PointFive and using Amazon DynamoDB pricing economics. This post explores how AWS, PointFive, and Nubank collaborated to turn cloud efficiency into a funding engine for resilience and AI innovation.

A major bottleneck for controlling Apache Spark costs or scaling analytics and AI workloads is Spark’s hard dependency on traditional CPU-only infrastructure. In this post, learn how DataPelago Accelerator for Spark closes that gap by seamlessly running your Spark workloads on heterogeneous hardware, delivering up to 10 times faster execution and up to 80% lower costs with zero code changes, no data migration, and no disruption to existing security configurations. See production results across social media, ecommerce, and financial services customers as you find out how to run a proof of concept on your own workloads.