Category: Analytics

Renewable energy operators face a growing challenge: Managing increasingly large, complex, high-value portfolios across solar, wind, and battery energy storage system (BESS) while meeting tighter compliance, grid, and market demands. Many operational workflows remain reactive, manual, and fragmented—limiting both performance and scalability. However, GreenBridge.AI is innovating renewable energy operations through AI agents for greater automated efficiency and scalability.

This post describes how BBVA used pilots to identify reusable ML patterns, standardize operational workflows, and design extensible MLOps templates that accelerate ML delivery while maintaining governance and flexibility across teams and business domains.

In this post, we present four production-hardening patterns (A-D) that extend Patterns 3 and 4 for payment workloads operating persistent session-based protocols. These patterns optimize connection reliability, maintenance workflows, tenant isolation, and observability at the infrastructure layer, benefiting organizations connecting to traditional payment rails through AWS PrivateLink and Resource Gateway.

Learn more about Amazon Web Services (AWS) Financial Services Symposium event that took place on May 7, 2026.

This is the first post in a two-part series exploring how AWS-native services, including Amazon Bedrock AgentCore, Amazon Neptune Analytics, Strands Agents, and a serverless data pipeline, power three transformative advisor capabilities:

This article focuses on the Amazon Managed Streaming for Apache Kafka (Amazon MSK) and Amazon Elastic Kubernetes Service (Amazon EKS) integration pattern that enable elastic, cost-efficient processing at scale.

In this blog post, learn more about Chuck Data which is a command-line AI agent for customer data, built by Amperity. It embeds years of customer data expertise and multi-patented identity resolution algorithms.

This blog will cover how PQD enables the transformation of after-sales vehicle quality from a reactive to a proactive, data-driven approach enabled by connected vehicle data, software-defined architectures, and AI/ML services from AWS.

Learn how to transform collections operations for banks and fintechs with AI and ML on AWS The Business Challenge Financial institutions face mounting pressure in collections operations. Traditional debt collection operates on a simple playbook: aggressive phone calls, generic messaging, and rule-based workflows. Yet customers have unique capacity to pay (income, assets, competing obligations), willingness […]

Autonomous Vehicles (AV) development has been maturing and is advancing through clear architectural changes: AV 1.0: classical modular stacks (perception → prediction → planning → control) with hand-engineered interfaces AV 2.0: multi-modal LLM end-to-end (E2E) learned stacks that reduce modularity and improve scaling with data AV 3.0: end-to-end reasoning VLA (Vision–Language–Action) systems that perceive, reason, […]