Category: Partner solutions

Managing AI costs is a top challenge for organizations scaling generative AI on AWS. This post shows how AWS CUR 2.0, Amazon S3, and AWS Trusted Advisor form the data foundation that New Relic Cloud Cost Intelligence builds on for Amazon Bedrock workloads. The result is token-level cost visibility inside the observability workflows engineering teams already use, shifting AI from opaque experimentation to disciplined, ROI-driven operations.

AI growth in regulated environments put pressure on the systems that govern your data. You need to give teams timely access to approved datasets without losing control of data placement, lineage, or reproducibility. In this post, we share three data architecture principles, show how Domino Data Lab applies them with Amazon FSx for NetApp ONTAP, and give you workload-level metrics to evaluate the architecture.

AI agents authenticate, hold permissions, and act on data, yet most organizations manage them as application components rather than governed identities. Learn how Saviynt Zuma works with Amazon Bedrock AgentCore to govern agents as first-class identities, from registration and least-privilege provisioning through runtime authorization, certification, and deprovisioning. Security teams can then answer which agents exist, who owns them, and what they can access.

The race to deploy agentic AI is outpacing the governance needed to put it into production – 74% of companies plan to deploy by 2027, yet only 21% have mature governance models. AWS launched GEAR (Governance Enabling Agentic Readiness) to close that gap, identifying partners whose governance accelerators compress months of setup into weeks and turn AI pilots into production-ready systems with measurable results.

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 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.

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.