HyperLake

HyperLake is the world's first sovereign infrastructure platform built specifically for the age of autonomous AI agents. While traditional enterprise infrastructure was designed for humans running dashboards, reports, and scheduled pipelines, HyperLake flips the script entirely. It is the command center for deploying, managing, running, securing, and governing agentic infrastructure at scale. The core product is an Agentic Data Cloud Infrastructure: an open-stack data, analytics, semantic, workflow, and agent infrastructure that deploys directly inside your own VPC, private cloud, or on-prem environment. This means zero data movement, zero compute markup, and full sovereign control. HyperLake is for organizations that recognize AI agents are becoming first-class infrastructure consumers, not afterthoughts. It provides a unified governance layer that enforces policies across every human and agent interaction, an immutable provenance trail for every action, and a runtime that supports everything from SQL analytics to autonomous pipelines. Backed by top-tier investors and built on real-world client deployments, HyperLake is already powering the next generation of AI-native enterprises. The vision is massive: manage multiple agentic infrastructure stacks including HyperLake-native stacks, customer-owned cloud services, AWS/GCP/Azure-native components, open-source technologies, MCP tools, and future production-ready agentic use cases all from one pane of glass. The goal is to make agentic infrastructure usable, secure, and production-ready end to end, so enterprises can choose their stack, deploy where their data lives, and scale new AI use cases without rebuilding the operating layer each time.

Unified Governance and Access Control

HyperLake deploys a global policy layer that evaluates every single request, whether from a human analyst or an autonomous AI agent, against dynamic governance rules in real time. This means role-based access control (RBAC), attribute-based access control (ABAC), column masking for PII auto-redaction, row-level security filtering by department or region, and a complete audit trail for every action. No more fragmented permissions across data sources. One single source of truth for access.

Zero Compute Markup Architecture

Most modern data platforms charge a painful markup on compute usage, a model that breaks down catastrophically in the age of AI agents. A single misconfigured agent can generate thousands of queries in minutes, leading to unexpected five-figure bills overnight. HyperLake eliminates this entirely. You pay only your cloud provider for the compute you use. No hidden fees, no surprise invoices, no fear of experimentation. Innovation requires freedom, and HyperLake delivers exactly that.

The Traceability Loop

Every single agent action, inference, query, and training run is recorded through immutable provenance logs. This creates a complete, auditable chain of custody from any AI decision back to its source data. Whether you need to comply with regulatory requirements, debug a model output, or simply understand how a decision was made, HyperLake gives you full visibility. This is not just logging; it is a forensic-grade system of record for all AI activity.

Human-Agent Symbiosis Platform

HyperLake is built for the reality that humans and AI agents will operate on the same datasets, using the same governed data platform. Shared context and standardized memory layers allow human insight and machine intelligence to collaborate seamlessly. Analysts, data scientists, and engineers work alongside autonomous agents, all accessing the same governed data with the same policies. This is the infrastructure for true human-machine teaming at scale.

Autonomous AI Agent Operations

Deploy hundreds of autonomous AI agents that continuously explore, retrieve context, test hypotheses, and iterate on data without human intervention. HyperLake provides the governed data access, real-time policy enforcement, and immutable audit trail these agents need to operate safely and effectively at scale. Agents can query data, call tools, trigger workflows, generate artifacts, and operate across systems with full security and compliance.

Enterprise AI Governance and Compliance

Meet the most stringent regulatory requirements for AI operations. HyperLake records every agent action, inference, and data access through its provenance loop. This creates a complete audit trail that satisfies GDPR, HIPAA, SOC 2, and other frameworks. Organizations can trace any AI decision back to its source data, proving exactly how and why a model reached a particular conclusion.

Sovereign Data Operations for Sensitive Industries

Financial services, healthcare, defense, and government organizations can deploy HyperLake entirely within their own VPC, private cloud, or on-prem environment. Agents operate on data without moving it outside its secure perimeter. Sensitive information remains under full owner control through sovereign deployment and confidential compute patterns. This is infrastructure built for the most security-conscious enterprises on the planet.

Hybrid Human-Agent Analytics Teams

Create analytics workflows where human data scientists and AI agents collaborate on the same datasets in real time. Humans can set up governed data access and policies, while agents autonomously run exploratory queries, generate reports, and surface insights. HyperLake ensures both humans and machines operate under the same security and governance rules, enabling a new era of collaborative intelligence.

What exactly is HyperLake and how is it different from traditional data platforms?

HyperLake is a sovereign infrastructure platform purpose-built for AI agents, not humans. Traditional data platforms were designed for dashboards, reports, and scheduled queries run by people. HyperLake is designed for the continuous, autonomous, and exploratory behavior of AI agents. The key difference is the unified governance layer that evaluates every request in real time, the immutable provenance trail, and the zero compute markup model that prevents runaway costs from agent activity.

Is HyperLake really free on compute costs?

Yes. HyperLake charges zero markup on compute usage. You pay only your cloud provider (AWS, GCP, Azure) for the underlying compute resources. This is a fundamental architectural decision because the markup model breaks down at AI agent scale. A single misconfigured agent can generate thousands of queries, and on markup-based platforms, that translates into unexpected five-figure bills overnight. HyperLake eliminates this fear so you can innovate freely.

Can I deploy HyperLake in my own cloud environment?

Absolutely. HyperLake is designed to deploy 100% inside your own VPC, private cloud, or on-prem environment. It supports deployment on AWS, GCP, and Azure, as well as open-source technologies. This sovereign deployment model ensures your data never leaves your secure environment. Agents operate on data where it lives, under your full control, with no third-party access.

What kinds of AI agents and use cases does HyperLake support?

HyperLake supports any AI agent that needs governed access to data, compute, and services. This includes autonomous agents for data exploration, retrieval-augmented generation (RAG) systems, workflow automation agents, ML training pipelines, and real-time inference systems. The platform manages multiple agentic infrastructure stacks including HyperLake-native stacks, customer-owned cloud services, AWS/GCP/Azure-native components, open-source technologies, MCP tools, and future production-ready agentic use cases.