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Elastic Achieves the AWS Agentic AI Specialization

Elastic has achieved the Amazon Web Services (AWS) Agentic AI Specialization, a new category launched within the AWS AI Competency. 

This specialization recognizes Elastic as an AWS Partner that enables customers to deploy smart, self-operating AI systems that can process, plan, and work independently to execute complex business processes.

The AWS AI Specialization in Agentic AI distinguishes Elastic as an AWS Partner with proven technical expertise and customer success in delivering production-ready autonomous AI systems that reason, plan, collaborate, utilize tools, execute tasks, and continuously improve. Elastic is providing deeply embedded agentic AI solutions using Amazon Bedrock AgentCore and other AWS-compatible frameworks like Strands. This helps customers move beyond experiments and deploy autonomous systems that deliver real, measurable value.

”The AWS Agentic AI Specialization is recognition of how the Elasticsearch platform for context engineering makes it easy to build AI agents that give the right answers and take the right actions,” said Alyssa Fitzpatrick, global vice president of Partner Sales at Elastic. “We use this robust platform to build agentic experiences into our product so that, for example, our Observability and Security customers can investigate and resolve issues fast.”

To make agentic AI more effective in real-world business settings, agents need to have the right context, which comes from scoping their actions and responses to post-training data locked away in silos across a company. Elasticsearch is an open, extensible context engineering platform that stores and searches structured and unstructured data and provides the retrieval and tool-building capabilities that agents need to successfully navigate complex tasks.

Elastic recently introduced Agent Builder, a set of capabilities powered by Elasticsearch, that makes it easy for developers to quickly build custom AI agents on their data. Agent Builder allows users to compose custom agents that use sophisticated tools for querying the relevant data, enabling conversation-based data exploration and automation. Agent Builder is built on Amazon Bedrock and utilizes reasoning models from the Anthropic family by default.

Amazon Agentic AI Specialization ensures customers can confidently select partners who demonstrate validated expertise in building and implementing enterprise-grade AI agents. These specialized partners help organizations deploy autonomous AI systems that can handle end-to-end business processes across diverse use cases, including enterprise knowledge operations, intelligent process automation, autonomous customer operations, financial operations automation, and supply chain optimization.

This expansion of the AWS AI Specialization now includes partners that demonstrate advanced capabilities delivering enterprise-ready generative AI and agentic AI systems to customers.

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Elastic Achieves the AWS Agentic AI Specialization

Elastic has achieved the Amazon Web Services (AWS) Agentic AI Specialization, a new category launched within the AWS AI Competency. 

This specialization recognizes Elastic as an AWS Partner that enables customers to deploy smart, self-operating AI systems that can process, plan, and work independently to execute complex business processes.

The AWS AI Specialization in Agentic AI distinguishes Elastic as an AWS Partner with proven technical expertise and customer success in delivering production-ready autonomous AI systems that reason, plan, collaborate, utilize tools, execute tasks, and continuously improve. Elastic is providing deeply embedded agentic AI solutions using Amazon Bedrock AgentCore and other AWS-compatible frameworks like Strands. This helps customers move beyond experiments and deploy autonomous systems that deliver real, measurable value.

”The AWS Agentic AI Specialization is recognition of how the Elasticsearch platform for context engineering makes it easy to build AI agents that give the right answers and take the right actions,” said Alyssa Fitzpatrick, global vice president of Partner Sales at Elastic. “We use this robust platform to build agentic experiences into our product so that, for example, our Observability and Security customers can investigate and resolve issues fast.”

To make agentic AI more effective in real-world business settings, agents need to have the right context, which comes from scoping their actions and responses to post-training data locked away in silos across a company. Elasticsearch is an open, extensible context engineering platform that stores and searches structured and unstructured data and provides the retrieval and tool-building capabilities that agents need to successfully navigate complex tasks.

Elastic recently introduced Agent Builder, a set of capabilities powered by Elasticsearch, that makes it easy for developers to quickly build custom AI agents on their data. Agent Builder allows users to compose custom agents that use sophisticated tools for querying the relevant data, enabling conversation-based data exploration and automation. Agent Builder is built on Amazon Bedrock and utilizes reasoning models from the Anthropic family by default.

Amazon Agentic AI Specialization ensures customers can confidently select partners who demonstrate validated expertise in building and implementing enterprise-grade AI agents. These specialized partners help organizations deploy autonomous AI systems that can handle end-to-end business processes across diverse use cases, including enterprise knowledge operations, intelligent process automation, autonomous customer operations, financial operations automation, and supply chain optimization.

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Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

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My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

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APMdigest's Predictions Series continues with 2026 DataOps Predictions — industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2026 ...

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