HyperLake

HyperLake is the command center for organizations preparing for a world where AI agents become primary users of infrastructure. Built by CerebrixOS, HyperLake provides sovereign, governed, and auditable infrastructure specifically designed for the agentic era. Unlike traditional platforms built for humans running dashboards and scheduled pipelines, HyperLake is architected for AI agents that query data, call tools, trigger workflows, generate artifacts, and operate continuously across systems. The first product wedge is 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 delivers a unified governance engine that evaluates every request from humans or agents against dynamic rules in real time. It offers $0 compute markup, meaning you only pay your cloud provider, eliminating the fear of unexpected bills from misconfigured agents generating thousands of queries. The platform is designed for enterprises that need to deploy, manage, run, secure, and govern agentic infrastructure at scale. HyperLake supports multiple stacks including HyperLake-native, 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, enabling enterprises to choose their stack, deploy where data lives, govern every interaction, audit every action, and scale new AI use cases without rebuilding the operating layer each time.

Unified Governance and Access Control

HyperLake provides a global policy layer that evaluates every request from humans or 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 filtering by department, region, or role, and a complete audit trail that version-tracks every action. Access is enforced consistently across data sources, queries, and context retrieval, ensuring that both human analysts and autonomous AI agents operate within the same governed framework without friction.

The Traceability Loop

Every agent action, inference, query, and training run is recorded through immutable provenance logs. HyperLake enables organizations to trace any AI decision back to its source data with complete auditability. This feature is critical for compliance, debugging, and trust. When an AI agent generates an output, you can instantly see which data sources it accessed, what queries it ran, and how it arrived at its conclusion. This creates a transparent, verifiable chain of custody for all agentic operations.

Data Sovereignty by Design

HyperLake allows agents to operate on data without moving it outside its secure environment. Sensitive information remains under full owner control through sovereign deployment and confidential compute patterns. The platform deploys 100% inside your cloud, VPC, or on-prem environment, ensuring data never leaves your controlled infrastructure. This is essential for regulated industries, enterprises with strict data residency requirements, and organizations handling sensitive intellectual property or personal data.

Human-Agent Symbiosis

Humans and AI agents operate on the same governed data platform with shared context and standardized memory layers. HyperLake enables human insight and machine intelligence to collaborate on the same datasets without compromising security or governance. Analysts, data scientists, and engineers work alongside autonomous and supervised AI agents, all accessing the same unified data layer through consistent policies. This symbiosis accelerates innovation by allowing teams to experiment freely while maintaining control.

Autonomous AI Agent Operations

Deploy AI agents that continuously explore data, retrieve context, test hypotheses, and iterate without human intervention. HyperLake provides the governed infrastructure for agents to query data, call tools, trigger workflows, and generate artifacts across systems. Organizations can run hundreds of agents simultaneously, knowing that every action is governed, audited, and traceable. This use case is ideal for enterprises building autonomous research systems, automated reporting pipelines, or AI-driven decision support platforms.

Governed Data Access for AI Agents and Humans

HyperLake serves as the system of access for both AI agents and human users. The unified governance engine ensures that every query, whether from a human analyst or an autonomous agent, is evaluated against the same dynamic policies. This eliminates the risk of agents bypassing security controls or accessing unauthorized data. Organizations can confidently enable AI agents to explore data while maintaining full compliance with internal policies and external regulations.

Sovereign AI Infrastructure Deployment

Deploy a complete, IaaC and GitOps-managed AI infrastructure in your own cloud environment. HyperLake provisions everything needed for AI-native operations, including governed data access, compute resources, and agent orchestration. With $0 compute markup, organizations only pay their cloud provider, eliminating the cost uncertainty that comes with markup-based platforms. This use case is perfect for enterprises that need to maintain data sovereignty while leveraging cutting-edge AI capabilities.

Multi-Stage Data Activation and Pipelines

HyperLake enables organizations to activate data from fragmented sources into governed, autonomous operations. The platform ingests and federates data from OLTP databases, cloud storage, open formats, streaming systems, SaaS APIs, and vector databases. The unified data layer then feeds into the governance engine, which controls access for humans, AI agents, and applications. Activated use cases include SQL analytics, ML and AI insights, dashboards and reports, real-time OLTP, data-as-a-service APIs, and autonomous pipelines.

How does HyperLake handle compute costs for AI agents?

HyperLake charges $0 compute markup, meaning you only pay your cloud provider for the compute resources used. This eliminates the financial risk of misconfigured agents generating thousands of queries and unexpected five-figure bills. Traditional markup-based platforms break down in the age of autonomous AI, but HyperLake ensures innovation requires freedom to experiment, not fear of the invoice.

Can HyperLake be deployed in my own cloud environment?

Yes, HyperLake deploys 100% inside your cloud, VPC, private cloud, or on-prem environment. The platform is designed for sovereign infrastructure, ensuring your data never leaves your controlled environment. HyperLake supports AWS, GCP, and Azure, as well as open-source technologies and customer-owned cloud services. This deployment model is ideal for regulated industries and enterprises with strict data residency requirements.

What kind of governance does HyperLake provide for AI agents?

HyperLake provides a global policy layer that evaluates every request from humans or agents against dynamic governance rules in real time. This includes role-based and attribute-based access control, column masking for PII auto-redaction, row-level security filtering, and complete audit trails. Every agent action, inference, query, and training run is recorded through immutable provenance logs, enabling full traceability from AI decisions back to source data.

How does HyperLake support both humans and AI agents on the same platform?

HyperLake enables human-agent symbiosis by providing shared context and standardized memory layers on the same governed data platform. Analysts, scientists, and engineers work alongside autonomous and supervised AI agents, all accessing the same unified data layer through consistent policies. This collaboration accelerates innovation while maintaining security and governance, allowing human insight and machine intelligence to operate together on data at scale.