Kiro is an Amazon Web Services (AWS) development environment based on artificial intelligence that uses an approach called spec-driven development, where software is built from requirements, architecture, and structured tasks.

Unlike other AI tools for programming, Kiro organizes development from the start, integrating:

In its most basic definition, cloud migration is moving workloads from on-premises environments to a cloud infrastructure managed by specialized vendors, such as Amazon Web Services.

However, in modern practice, it implies something much more strategic: redesigning the technological architecture so that it is scalable, resilient, aligned with business objectives and the new technologies of the current context.

A well-executed migration is noticeable because:

Traditional automation works with predefined rules. If something happens, the system responds according to a programmed instruction. It’s efficient, of course, but its capabilities are limited when environments change.

On the other hand, Agentic AI is an artificial intelligence model based on autonomous agents capable of receiving a business objective, analyzing the context, making decisions and executing actions to achieve it, adjusting as it learns.

This digital evolution allows business processes to be adjusted in real time without losing governance.

Anthropic es reconocida por su fuerte enfoque en el desarrollo de modelos fundacionales de IA, con un compromiso claro hacia:

• Model Security and Alignment
• Responsible use of AI
• Reliability in enterprise environments
• Governance and control

Its Claude model, which is now available through Amazon Bedrock, will undoubtedly enable organizations to integrate advanced generative AI capabilities within secure, scalable, and fully managed architectures on AWS.

Amazon AI AgentOps is a service we’ve designed to create governed business agents that don’t just analyze or converse, but execute actions directly on top of your organization’s internal systems.

Its design combines three fundamental pillars:

One of the great benefits of artificial intelligence is the ability to automate repetitive and operational tasks. Not only does this streamline workflows, but it also frees up human talent to focus on higher-impact activities.

AI case study: NAD Global, a foreign trade company, reduced invoice processing time from days to minutes thanks to an automatic extraction system based on Amazon Bedrock. In addition to speed, they managed to optimize key human resources.

Let’s be clear: an Artificial Intelligence (AI) project seeks to get a machine to perform tasks that a human would normally do. We are referring to understanding language, seeing images, analyzing feelings or making decisions with context.

For example, think of a chatbot that not only responds with pre-programmed phrases, but understands what you’re asking —even if you don’t use the exact words— and gives you a useful answer. Or imagine a camera that detects whether a person is happy, confused, or upset. All of this enters the world of artificial intelligence.

Technically, an AI project can use:

That today you can count on an AWS Certified Partner in Generative AI, ready to guide you through the entire adoption cycle: from initial experimentation to building robust enterprise applications.

Whether you’re looking to automate tasks, personalize experiences, optimize internal processes, or innovate with new business models, the AWS Generative AI Competency confirms that Itera has the expertise and validation to make it possible.

In the Well-Architected Framework, each pillar represents a critical dimension to build robust, scalable, and sustainable solutions in the cloud. These are:

Here are 4 reasons why more and more companies are betting on VMware Cloud on AWS with the support of a certified partner like us.