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Private AI on Cloudera

Production AI on the data you can't move.

Run the full inference stack inside your perimeter — prompts, proprietary data, and outputs never leave. Built on the governed Cloudera estate your regulators already accept, and delivered to clear model-risk and audit, not just the demo.

Why pilots stall

The demo works. The review kills it.

Your team builds something impressive — then it hits model-risk, the CISO, or compliance, and the answer is no, because the data went somewhere it can't go.

The fix isn't a better demo. It's an architecture where regulated data never leaves your control, every model action is traceable, and the evidence to approve it is produced as part of delivery. That's what private AI on Cloudera is.

The architecture

One governed stack, entirely inside your boundary.

Cloudera's principle is to bring AI compute to the data instead of moving data to the AI. Every layer below runs in your environment — on-prem or private cloud.

Your security perimeter
Agents & applications Cloudera Agent Studio — orchestrated, sandboxed, auditable workflows
application
Model layer — model-agnostic NVIDIA Nemotron · Llama · Mistral · Cohere · your fine-tuned models
models
Cloudera AI Inference · NVIDIA NIM High-performance model serving inside the perimeter — no egress
compute
Cloudera Data Platform + SDX Governed data with lineage, Ranger access control, Atlas catalog
governed data
No prompt, document, or output crosses this boundary.
How we deliver

We deliver the use case — and the evidence to approve it

The platform is Cloudera's and NVIDIA's. What gets you to production is the domain depth and delivery judgment to satisfy the people whose job is to say no. That's the part we own.

STEP 01

Readiness & scope

A fixed-scope assessment of your data, governance, and the target use case — so the build starts on solid ground and the risks are known up front.

STEP 02

Build in-perimeter

Stand up Cloudera AI Inference with NVIDIA NIM, wire in your governed data, and build the use case with grounded, citation-backed outputs.

STEP 03

Clear the review

We produce the lineage, controls, and traceability your model-risk, CISO, and examiner reviews require — and move it into production.

Where it lands first

Two production-ready starting points

Banking & financial services

AML investigator copilot

An in-perimeter copilot that triages financial-crime alerts — pulling transaction history, KYC records, prior filings, and adverse media into one place and drafting the investigation narrative, with every claim cited to source.

Clears examiner & model-risk review · speeds alerts, doesn't replace judgment
Healthcare & med devices

PHI-safe document intelligence

In-perimeter summarization and Q&A over PHI-laden records — clinical-note summarization, prior-authorization drafting, or adverse-event triage — with grounded, cited answers reviewers can trust.

PHI never leaves the perimeter · built to clear HIPAA review
Frequently Asked Questions

Private AI on Cloudera, answered

What is private AI on Cloudera? +

Private AI runs the entire inference stack inside your security perimeter, so prompts, proprietary data, and model outputs never leave your environment. On Cloudera, it's delivered through Cloudera AI Inference powered by NVIDIA NIM, served on top of governed data in the Cloudera Data Platform.

Does my data leave my environment? +

No. Cloudera brings AI compute to the data rather than sending data out to an external model. Models are served in-perimeter — on-prem or in your private cloud — so regulated data stays inside your control and never reaches a public model endpoint.

Which models can run on it? +

It's model-agnostic. Open and commercial models such as NVIDIA Nemotron, Llama, and Mistral, enterprise models such as Cohere, and your own fine-tuned models can all be served in-perimeter. We help you choose and govern the right model for each regulated use case rather than locking you to one vendor.

How does it clear model-risk and audit review? +

Cloudera SDX provides lineage and access controls, and grounded, citation-backed outputs trace every answer to its source data. Combined with our delivery practices, that produces the evidence model-risk, CISO, and examiner reviews need to approve a deployment.

The low-risk first step

See if your data is ready for private AI

A fast, fixed-scope AI Readiness Assessment tells you exactly what stands between your stalled pilot and a production deployment your auditors will sign off on.