Resilience, accelerated AI transformation based on agents... "Context engineering" is the key

As intelligent automation becomes the next battleground for artificial intelligence development, Elastic CEO Ash Kulkarni emphasized at AWS re:Invent 2025 that enterprises are rapidly shifting toward agent-based systems, or “agentic AI.” At the core of this trend is “context engineering,” which is surpassing mere data analysis to become the decisive factor in ensuring AI model accuracy.

Elastic possesses foundational technology capable of rapidly connecting unstructured data such as documents, logs, and messages within enterprise systems to build context. CEO Kulkarni stated, “Any model’s training data is limited to public data. In actual business scenarios, the key is to use each enterprise’s private data to build context and connect it to the model.” Elastic automates this process through integration with AWS “AgentCore,” laying the groundwork for building AI agents that can be applied to real-world business use cases.

Elastic is also advancing enterprise AI workflow development in partnership with Accenture, with this integrated solution available directly through AWS Marketplace. Notably, Elastic is among the first independent software vendors to receive AWS “AI Competency Certification,” formally recognizing its context-based AI development capabilities.

Currently, as the center of AI infrastructure shifts from servers or cloud infrastructure to the data itself, Elastic has begun transitioning toward a “data cloud.” CEO Kulkarni emphasized, “The real differentiator in AI is no longer the model. The winning move lies in the data layer that can organically and meaningfully connect structured and unstructured data.” He added, “Elastic will give context to this vast and disordered data to support enterprises in leading the new AI era.”

Elastic currently supports a wide range of data integration architectures, from open models like LLaMA and Mistral to proprietary models developed by OpenAI, Google, Nvidia, and others. The context engine built on this foundation is becoming the core tool for enterprises to achieve tangible automation results in the rapidly evolving AI market.

This approach goes beyond merely adding intelligence to existing AI, aiming instead to build a “agentic cloud” that operates centered on data. Elastic analysis suggests that agent-based systems will ultimately account for more than 80-90% of the impact of AI adoption, and the company is confident its platform will play a central role in this core technological transformation.