HyperLake

HyperLake is an advanced infrastructure platform designed to empower organizations preparing for an era where AI agents play a pivotal role in data management and operational processes. Unlike traditional enterprise infrastructure, which is tailored for human users through dashboards and scheduled tasks, HyperLake focuses on the unique needs of AI agents. These agents demand constant access to governed data, compute resources, and workflow automation to perform autonomous tasks effectively. HyperLake serves as a command center that facilitates the deployment, management, and governance of this new agentic infrastructure. Its core offering, the Agentic Data Cloud Infrastructure, can be deployed in a customer's private cloud or VPC, ensuring that organizations maintain control over their data while utilizing AI to drive innovation. The broader vision encompasses multiple infrastructure stacks, enabling seamless integration with existing cloud services and open-source technologies, ultimately making AI-driven operations secure, scalable, and production-ready.

Unified Governance & Access

HyperLake offers a robust governance framework that evaluates every request—whether from humans or AI agents—against real-time dynamic governance rules. This ensures consistent enforcement of access controls across various data sources and contextual retrievals.

The Traceability Loop

Every action performed by AI agents is meticulously recorded through immutable provenance logs. This feature provides complete auditability, enabling organizations to trace any AI decision back to its source data, ensuring transparency and accountability.

Data Sovereignty by Design

HyperLake allows AI agents to process data without transferring it outside its secure environment. This feature ensures that sensitive information remains under full control of the organization, aligning with data sovereignty regulations and enhancing security.

Human-Agent Symbiosis

The platform enables seamless collaboration between humans and AI agents on the same governed data environment. By providing shared context and standardized memory layers, HyperLake fosters a productive partnership where human insights complement machine intelligence.

Autonomous Data Exploration

Organizations can leverage HyperLake for AI agents to autonomously explore vast datasets. This capability allows for continuous retrieval and context generation, driving insights and innovation without human intervention.

Real-Time Analytics

HyperLake enables real-time analytics where AI agents can generate immediate insights from data streams. This use case is crucial for businesses that need timely information for decision-making and operational efficiency.

Secure Data Sharing

With HyperLake, enterprises can share sensitive data securely among AI agents without compromising data sovereignty. This feature is essential for compliance with regulations while still leveraging AI capabilities.

Automated Workflow Management

HyperLake facilitates the automation of complex workflows through AI agents. By integrating with various tools and services, organizations can streamline their operations and reduce manual overhead.

What distinguishes HyperLake from traditional data platforms?

HyperLake is specifically designed for AI agents, offering a governance framework and infrastructure that supports continuous data retrieval and autonomous operations, unlike traditional platforms that focus on human-centric tasks.

How does HyperLake ensure data security?

HyperLake employs data sovereignty by allowing AI agents to operate on data within its secure environment. This minimizes the risk of data breaches and ensures compliance with regulatory requirements.

Can HyperLake integrate with existing cloud services?

Yes, HyperLake is built to manage multiple infrastructure stacks, including customer-owned cloud services and components from major providers like AWS, GCP, and Azure, ensuring seamless integration with existing systems.

What is the pricing model for HyperLake?

HyperLake operates on a $0 compute markup model, meaning organizations only pay for the underlying cloud provider's compute resources, eliminating unexpected costs associated with traditional pricing models.