Sovereign AI, delivered where your data lives
You bring a business problem. Thirty days later a governed AI application is in production, on GPU and CPU in our data center, your data center or your cloud. One stack, one company accountable, and your data never leaves your jurisdiction.
Data
ComputeNVIDIAAMDNeoclouds rent GPUs. Enterprises don't need more GPU hours. They need the data connected, the policy enforced and the application built. On infrastructure they're allowed to use.
Banks, insurers, health systems, agencies and telcos can rent a cluster tomorrow. It doesn't help. Their data sits in forty systems, every AI project re-litigates privacy, and nobody builds the application. So we sell the whole stack, from silicon to screen, as one outcome.
Every engagement is a fixed-scope sprint that ends with an application in production, then grows into a subscription and dedicated compute.
Subscriber, network and incident data across OSS/BSS, with emergency-location requirements.
Sources virtualized, location and subscriber fields classified, redaction rules applied.
HLR Finder, the Osprey emergency locator and network provisioning in production. These run on PIES for customers today.
Core banking, cards and CRM in separate systems. Privacy and model-risk review block every AI pilot.
Zetaris maps the estate in place. PCI and privacy policy applied; PII never reaches a model unredacted.
A triage application and agent on a private model in the bank's own data center, every call in a verifiable audit chain your model-risk team can review.
Patient records, scheduling and claims data under health-privacy law, with no approved path to a frontier model.
Deployed into the health system's own Azure tenancy; health-privacy template (HIPAA in the US); patient data redacted before any model sees a record.
A documentation assistant for clinicians, on a private model, with an MCP server for approved agents.
Bank and health-system rows are sprint templates, not named customer engagements.
Describe the application; PIES builds the data model, screens and logic, then deploys it as a real container.
Your whole estate, queried where it lives. A semantic layer tells policy what every field is.
Dedicated GPU and CPU in our region, your data center or your cloud account. We specify it, supply it and run it.
Where it runs
The outcome is the same wherever it runs. Choose by where your data lives, what your regulator expects and what you have already paid for.
Dedicated GPU and CPU in an IntelligentX region in your country, operated by our staff there. Nothing to buy, nothing to run.
We deliver a validated reference rack, NVIDIA and AMD on Dell or Supermicro, install it in your facility and operate it remotely, or hand it over fully air-gapped.
The stack deploys into your own cloud tenancy on GPU instances, in the region you choose, drawing down the commitment you already have.
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