Platform

An intelligence-ready cloud stack

IntelligentX delivers the infrastructure and the two layers above it. Zetaris is the data layer. PIES Studio is the application layer. All three run where you choose: an IntelligentX region, your own data center, or your AWS or Azure account.

AppsPIES StudioPIES StudioDataZetarisComputeNVIDIAAMDDellSupermicro
B200 Apps · PIES StudioData · ZetarisCompute · NVIDIA GPU + AMD CPU

Application layer

PIES Studio

Describe an application in business terms. PIES plans the data model, builds the screens, wires the logic, and deploys it as a real container.

Build

AI-native application generation

React, Angular, Go, Python and Java. Real container previews while you build, then Kubernetes deployment. Every change the AI makes is an ordinary object you can open, edit or rewind.

Model

A private LLM family

The PIES private model family runs on your own GPUs and can be tuned with LoRA on your data, so answers follow your standards. Governance policy decides when a workload uses a private model and when it uses an approved cloud model from Anthropic, OpenAI, Azure OpenAI or xAI.

Agents

An MCP server for every application

Generated automatically on deploy. Agents get the application's data and actions, and Zetaris supplies the business context they need to act safely.

Operate

Governance policies and a verifiable audit chain

Model routing is set centrally, never by an individual session. Every AI call is recorded with the model, policy and data classification, in a tamper-evident chain you can verify on demand.

Data layer

Zetaris

The semantic context agents and models need, without a data migration.

Virtualize

Any JDBC source, in place

Core banking, cards, CRM, claims, operational systems. Data stays where it lives and is queried through one layer.

Classify

A semantic layer that knows what each field is

Fields are classified automatically across every connected system, so policy knows what it is protecting before a prompt is ever written.

Protect

PII redaction before any cloud model

Sensitive values are redacted inside the sovereign boundary. An audit log records every call, so regulators see what was asked and what was answered.

Infrastructure layer

GPU and CPU, region by region

NVIDIAAMDDellSupermicro

The same NVIDIA and AMD reference design in three places: an IntelligentX region, your data center, or GPU instances in your own cloud. Compare the options → Full infrastructure detail →

GPU

NVIDIA Blackwell, sized for inference

HGX B200 nodes for fine-tuning and the larger private models. RTX PRO 6000 Blackwell servers for dense, air-cooled inference of the Lite and Dev models.

CPU

AMD EPYC for apps and data

Kubernetes clusters on EPYC servers run the PIES and Zetaris platforms, every generated application and its database. Most enterprise workload is CPU, so we sell it as a first-class product, not an afterthought.

Tenancy

Dedicated and pinned to your jurisdiction

In our regions, each tenant stays in one country, operated by staff there. In your data center or cloud, it stays where you put it. Zetaris policy enforcement on every call, everywhere.

Economics

Private inference with no per-token fee

No per-token charges, no data egress, unlimited inference on your dedicated capacity. Agents make many small calls; on dedicated nodes that cost is flat.

Governance

Policy enforced at the platform, not per project

Regulated industries buy governed AI as one thing instead of assembling it from separate tools. HIPAA, PCI, air-gapped and sovereign templates come built in.

  • 01
    ClassifyEvery connected field is classified through the Zetaris semantic layer.
  • 02
    RedactSensitive values never leave the sovereign boundary.
  • 03
    RouteGovernance policies decide which model handles which workload.
  • 04
    AuditA tamper-evident chain for every AI call, verifiable on demand.

See it

Bring one data estate and one problem.

We will show the platform generating, governing and deploying against your own context.

Book a session →