deploy, manage, run, secure, and govern that agentic infrastructure. The first product wedge is Agentic Data Cloud Infrastructure: open-stack data, analytics, semantic, workflow, and agent infrastructure deployed inside the customer’s own VPC, private cloud, or on-prem environment.

But the broader vision is larger than one stack. HyperLake is designed to manage many agentic infrastructure stacks: HyperLake-native stacks, customer-owned cloud services, AWS/GCP/Azure-native components, open-source technologies, governed data services, workflow systems, MCP tools, and future production-ready agentic use cases.

The goal is to make agentic infrastructure usable, secure, and production-ready end to end. Enterprises should be able to choose the stack, deploy it where their data lives, govern every human and agent interaction, audit every action, and scale new AI use cases without rebuilding the operating layer each time.

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HyperLake is built for organizations preparing for a world where AI agents become primary users of infrastructure.

Today, most enterprise infrastructure was designed for humans, dashboards, applications, and scheduled pipelines. AI agents behave differently. They query data, call tools, trigger workflows, generate artifacts, operate across systems, and need continuous access to governed compute, data, policies, and services.

HyperLake provides the command center to deploy, manage, run, secure, and govern that agentic infrastructure. The first product wedge is Agentic Data Cloud Infrastructure: open-stack data, analytics, semantic, workflow, and agent infrastructure deployed inside the customer’s own VPC, private cloud, or on-prem environment.

But the broader vision is larger than one stack. HyperLake is designed to manage many agentic infrastructure stacks: HyperLake-native stacks, customer-owned cloud services, AWS/GCP/Azure-native components, open-source technologies, governed data services, workflow systems, MCP tools, and future produ

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