HyperLake — Sovereign AI Factory Inside Your Own Cloud
Give your enterprise and your clients sovereign intelligence they actually own. HyperLake is a hardened, container-based private AI factory that runs inside your own cloud account — your data, your apps, your agents, your models, your keys, at any scale. One-click solution packs deploy data, models and agents in minutes.
The problem
Teams taking AI into production do not lack models — they lack a governed environment to run them in. Every project rebuilds identity, network isolation, policy, secrets, audit and lineage from scratch, and each new workload restarts the security review. HyperLake makes that posture a property of the environment, so every workload inherits it.
What HyperLake provides
- Hardened container substrate deployed inside your own cloud account or your customer's
- Cryptographic workload identity and default-deny network isolation
- Policy-as-code admission and runtime enforcement, with scoped short-lived secrets
- Role- and attribute-based access to data, full audit trails and lineage
- Lifecycle operations — patching, upgrades and self-managing operations
- Zero compute markup: billed directly by your cloud provider
One substrate. Interchangeable solution packs.
The substrate never changes; everything above it does. Solution packs — data and execution (Trino, Iceberg, PostgreSQL), model infrastructure, and more over time — are optional and swappable. Take one, bring your own, or take none and use the hardened substrate purely as the place your own applications run.
Control surface — Cursor for Sovereign AI
Your sovereign infrastructure is one call away: ask in chat, run in CI, type it yourself, or drive it from the HyperLake app UI. Everything HyperLake does is callable through a CLI and an MCP-compatible toolset — creating clusters, installing apps, publishing catalogs, running security checks. Every action is authenticated with JWT, authorised against your policies, and written to an immutable audit log.
Who it is for
Enterprises running AI transformation programmes, forward-deployed engineering teams shipping into customer environments, agent and AI product companies that need a governed runtime, and AI-native managed service providers building a repeatable operating foundation with recurring platform revenue.
Deployment
Cloud-agnostic: AWS, Azure, Google Cloud, OVH, private cloud, on-premise hardware, or fully air-gapped estates. The governance and audit posture is identical wherever it lands.
Blog — data and AI infrastructure insights
Contact: hyperlake.cloud