HyperLake

HyperLake is a sovereign infrastructure platform designed for organizations preparing for a world where AI agents become primary consumers of enterprise infrastructure. Unlike traditional platforms built for humans running dashboards, reports, and scheduled queries, HyperLake provides the command center to deploy, manage, run, secure, and govern agentic infrastructure. The product delivers an Agentic Data Cloud Infrastructure: an open-stack data, analytics, semantic, workflow, and agent infrastructure deployed inside the customer's own VPC, private cloud, or on-prem environment. HyperLake is built for enterprises that need AI agents to query data, call tools, trigger workflows, generate artifacts, and operate across systems with continuous access to governed compute, data, policies, and services. The platform manages multiple agentic infrastructure stacks including 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. With $0 compute markup, 100% deployment in your cloud, governance by design, and self-serve plus expert-led onboarding, HyperLake eliminates the compute tax problem where a single misconfigured agent can generate thousands of queries resulting in unexpected five-figure bills. The platform ensures data sovereignty by design, immutable provenance logs for every agent action, and a unified governance layer that evaluates every request against dynamic rules in real time.

Unified Governance and Access Control

A global policy layer that evaluates every request from humans or AI agents against dynamic governance rules in real time. This feature enforces role-based access control (RBAC), attribute-based access control (ABAC), column masking for PII auto-redaction per role, row-level security filtered by department, region, or role, and complete audit trails with every action version-tracked. Access is enforced consistently across data sources, queries, and context retrieval operations.

The Traceability Loop

Every agent action, inference, query, and training run is recorded through immutable provenance logs. This feature enables organizations to trace any AI decision back to its source data with complete auditability. The traceability loop provides a complete historical record of how agents interact with data, what queries were executed, what context was retrieved, and what artifacts were generated, ensuring full compliance and accountability.

Data Sovereignty by Design

Agents can operate on data without moving it outside its secure environment. Sensitive information remains under full owner control through sovereign deployment and confidential compute patterns. HyperLake ensures data never leaves the customer's cloud environment, with 100% deployment in your own VPC, private cloud, or on-prem infrastructure. This feature is critical for regulated industries requiring data residency and compliance.

Human-Agent Symbiosis

Humans and AI agents operate on the same governed data platform with shared context and standardized memory layers. This feature allows human insight and machine intelligence to collaborate on the same datasets, enabling analysts, data scientists, and engineers to work alongside autonomous and supervised AI agents. Shared context ensures that both human and agent decisions are based on the same governed data foundation.

Autonomous AI Agent Operations

Enterprises deploying autonomous AI agents that continuously explore data, retrieve context, test hypotheses, and iterate can use HyperLake as the governed system of access. The platform ensures that agents can query data, call tools, trigger workflows, and generate artifacts without incurring unexpected compute costs or compromising data security. The $0 compute markup model eliminates the financial risk of misconfigured agents generating thousands of queries.

Governed Data Access for Regulated Industries

Organizations in finance, healthcare, and government can deploy HyperLake to provide AI agents with governed access to sensitive data while maintaining full compliance. The unified governance layer enforces RBAC, ABAC, column masking, and row-level security in real time, ensuring that agents only access data they are authorized to see. Immutable provenance logs provide complete auditability for regulatory requirements.

Multi-Stack Agentic Infrastructure Management

Large enterprises with complex infrastructure spanning HyperLake-native stacks, cloud-native components, open-source technologies, and governed data services can use HyperLake as a single command center. The platform manages multiple agentic infrastructure stacks, enabling organizations to choose the stack, deploy it where their data lives, govern every human and agent interaction, and scale new AI use cases without rebuilding the operating layer each time.

Real-Time AI-Driven Analytics and Insights

Data teams can use HyperLake to enable AI agents to perform real-time SQL analytics, machine learning insights, and dashboard reporting on governed data. The platform supports ingestion from OLTP databases, cloud storage, open formats like Iceberg and Delta, streaming systems, SaaS APIs, and vector databases. Agents can autonomously explore data and generate insights while the governance engine ensures every query is authorized and audited.

What is HyperLake and who is it for?

HyperLake is sovereign infrastructure for AI agents, built for organizations where AI agents are first-class infrastructure consumers. It is designed for enterprises that need to deploy, manage, run, secure, and govern agentic infrastructure inside their own VPC, private cloud, or on-prem environment. The platform is ideal for organizations in regulated industries, large enterprises managing complex multi-stack environments, and any company deploying autonomous AI agents that need governed access to data and compute resources.

How does HyperLake eliminate the compute tax problem?

Most modern data platforms charge a markup on compute usage, which breaks down in the age of autonomous AI. A single misconfigured agent can generate thousands of queries in minutes, resulting in unexpected five-figure bills. HyperLake charges $0 compute markup, meaning you only pay your cloud provider for the compute resources used. This model enables innovation without fear of the invoice and allows organizations to experiment freely with AI agents at scale.

How does HyperLake ensure data sovereignty and security?

HyperLake ensures 100% deployment in your cloud environment, whether that is your VPC, private cloud, or on-prem infrastructure. Data never leaves your secure environment. The platform features a global governance layer that evaluates every request against dynamic rules in real time, including RBAC, ABAC, column masking, and row-level security. Immutable provenance logs record every agent action, inference, query, and training run for complete auditability and compliance.

Can HyperLake manage existing cloud-native and open-source components?

Yes, HyperLake is designed to manage many agentic infrastructure stacks beyond its native stack. The platform supports 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. This flexibility allows enterprises to choose their preferred stack and deploy it where their data lives without being locked into a single vendor ecosystem.