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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.

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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UK IT leaders are reaching a critical inflection point in how they manage observability, according to research from LogicMonitor. As infrastructure complexity grows and AI adoption accelerates, fragmented monitoring environments are driving organizations to rethink their operational strategies and consolidate tools ...

For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

AI can't fix broken data. CIOs who modernize revenue data governance unlock predictable growth-those who don't risk millions in failed AI investments. For decades, CIOs kept the lights on. Revenue was someone else's problem, owned by sales, led by the CRO, measured by finance. Those days are behind us ...

Over the past few years, organizations have made enormous strides in enabling remote and hybrid work. But the foundational technologies powering today's digital workplace were never designed for the volume, velocity, and complexity that is coming next. By 2026 and beyond, three forces — 5G, the metaverse, and edge AI — will fundamentally reshape how people connect, collaborate, and access enterprise resources ... The businesses that begin preparing now will gain a competitive head start. Those that wait will find themselves trying to secure environments that have already outgrown their architecture ...

Ask where enterprise AI is making its most decisive impact, and the answer might surprise you: not marketing, not finance, not customer experience. It's IT. Across three years of industry research conducted by Digitate, one constant holds true is that IT is both the testing ground and the proving ground for enterprise AI. Last year, that position only strengthened ...

A payment gateway fails at 2 AM. Thousands of transactions hang in limbo. Post-mortems reveal failures cascading across dozens of services, each technically sound in isolation. The diagnosis takes hours. The fix requires coordinated deployments across teams ...

Every enterprise technology conversation right now circles back to AI agents. And for once, the excitement isn't running too far ahead of reality. According to a Zapier survey of over 500 enterprise leaders, 72% of enterprises are already using or testing AI agents, and 84% plan to increase their investment over the next 12 months. Those numbers are big. But they also raise a question that doesn't get asked enough: what exactly are companies doing with these agents, and are they actually getting value from them? ...

Many organizations still rely on reactive availability models, taking action only after an outage occurs. However, as applications become more complex, this approach often leads to delayed detection, prolonged disruption, and incomplete recovery. Monitoring is evolving from a basic operational function into a foundational capability for sustaining availability in modern environments ...

In MEAN TIME TO INSIGHT Episode 22, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses DNS Security ... 

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