HyperLake

HyperLake is the sovereign infrastructure command center built for organizations preparing for a world where AI agents become the primary consumers of enterprise infrastructure! This is a radical shift from the legacy world of dashboards, reports, and scheduled pipelines designed exclusively for humans. AI agents behave completely differently. They query data continuously, call tools, trigger workflows, generate artifacts, and operate across multiple systems simultaneously. They need relentless, governed access to compute, data, policies, and services. HyperLake provides the complete operating system to deploy, manage, run, secure, and govern that new agentic infrastructure. The first major product wedge is the Agentic Data Cloud Infrastructure: an open-stack combination of data, analytics, semantic, workflow, and agent infrastructure deployed directly inside the customer's own VPC, private cloud, or on-prem environment. But the vision is much larger than one stack! HyperLake is designed to manage many 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. The ultimate goal is to make agentic infrastructure usable, secure, and production-ready end to end. Enterprises can choose their 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. It is the AI Factory for Autonomous Agents!

Unified Governance and Access Control

HyperLake features a global policy layer that evaluates every single request whether it comes from a human or an AI agent against dynamic governance rules in real time! This means access is enforced consistently across all data sources, queries, and context retrieval operations. No more fragmented security policies across different tools. Role-based access control (RBAC), attribute-based access control (ABAC), column masking for automatic PII redaction, and row-level security filters all work together to create a bulletproof governance framework for the agentic age.

The Complete Traceability Loop

Every single agent action, inference, query, and training run is recorded through immutable provenance logs! This feature creates a complete audit trail that allows organizations to trace any AI decision back to its source data with full accountability. If an agent makes a questionable decision or generates an unexpected output, you can instantly replay the entire chain of events. This is critical for compliance, debugging, and building trust in autonomous systems operating on sensitive enterprise data.

Data Sovereignty by Design

HyperLake enables agents to operate on data without ever moving it outside its secure environment! Sensitive information remains under the full control of the data owner through sovereign deployment patterns and confidential compute capabilities. You deploy HyperLake inside your own cloud account, VPC, or on-premises data center. Your data never leaves your controlled environment. This is sovereign infrastructure for AI agents by default, not as an afterthought.

Human-Agent Symbiosis Platform

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 seamlessly on the same datasets. Analysts, data scientists, and engineers work alongside autonomous agents, all accessing the same governed data through the same policy layer. This creates a unified operating environment where human expertise and AI scale work together without friction or security gaps.

Autonomous AI Agent Operations

Deploy and manage hundreds of autonomous AI agents that continuously explore, retrieve context, test hypotheses, and iterate on enterprise data! HyperLake provides the governed runtime these agents need to operate without fear of runaway compute costs or data breaches. Agents can query multiple data sources, call external tools, trigger workflows, and generate artifacts all while being tracked by the immutable audit trail. This is the infrastructure backbone for production-ready autonomous agent fleets.

Governed Self-Service Analytics for Humans and Agents

Enable both human analysts and AI agents to perform SQL analytics, generate dashboards, and create reports on the same governed data platform! Traditional analytics tools break down when agents start querying thousands of times per day. HyperLake ensures every query is governed, every result is auditable, and compute costs are transparent with zero markup. Organizations can finally give both humans and agents the freedom to explore data without fear of unexpected bills or security violations.

Real-Time Context Retrieval for AI Applications

Power AI applications and chatbots with real-time, governed context retrieval from your enterprise data sources! Whether an agent needs to pull customer history from PostgreSQL, analyze streaming data from Kafka, or query vector embeddings from pgVector, HyperLake provides the unified data layer. Every context retrieval is logged and governed, ensuring sensitive information is never exposed to unauthorized agents or applications.

Multi-Stack Agentic Infrastructure Management

Manage and govern multiple agentic infrastructure stacks from a single command center! Organizations can run HyperLake-native stacks alongside AWS/GCP/Azure-native components, open-source technologies, and legacy systems. The unified governance layer applies consistent policies across all stacks. This allows enterprises to adopt the best technology for each use case without creating fragmented security and management silos. Scale new AI use cases without rebuilding the operating layer each time.

What exactly is HyperLake and who is it for?

HyperLake is a sovereign infrastructure platform purpose-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 cloud environment. This includes data teams, AI engineering teams, platform engineering teams, and security teams who are building production-ready AI systems. If your organization is moving beyond simple chatbots into autonomous agents that continuously interact with your data and systems, HyperLake is the command center you need.

How does HyperLake prevent runaway compute costs from AI agents?

HyperLake operates on a zero compute markup model! You pay only your cloud provider for the underlying compute resources. This eliminates the fear of unexpected five-figure bills when a misconfigured agent generates thousands of queries in minutes. Traditional data platforms charge markup on compute usage, which breaks down completely in the age of autonomous AI. With HyperLake, innovation requires freedom to experiment, not fear of the invoice. At scale, when hundreds of agents iterate and retry simultaneously, this cost model is a game changer.

Can HyperLake work with my existing cloud infrastructure?

Absolutely! HyperLake is designed to be deployed 100% inside your own cloud environment including AWS, GCP, Azure, private cloud, or on-premises data centers. It integrates with your existing cloud-native components, open-source technologies, and legacy systems. The platform manages many agentic infrastructure stacks simultaneously, so you are not locked into a single vendor or architecture. You choose the stack, deploy it where your data lives, and govern everything from one command center.

How does HyperLake ensure data security and compliance for AI agents?

HyperLake provides a global policy layer that evaluates every request from humans and agents against dynamic governance rules in real time. This includes role-based and attribute-based access control, automatic PII redaction through column masking, row-level security filters, and a complete immutable audit trail for every action. Data sovereignty is built in by design, meaning agents operate on data without moving it outside its secure environment. Every agent action, inference, query, and training run is recorded through immutable provenance logs, ensuring complete auditability for compliance requirements.