Private AI Infrastructure

Your compliance team isn't blocking AI to be difficult.
They're blocking it because nobody's built
something they can say yes to.

Ark33 deploys enterprise-grade AI on your own infrastructure. Your data stays inside your perimeter — during deployment, during inference, always. For regulated industries where cloud AI isn't an option, this is the alternative.

Schedule a Compliance Risk Assessment → Free 20-minute call. Honest read on your exposure. No pitch.
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Zero Data EgressYour data never leaves your perimeter
Compliance-First ArchitectureBuilt for NERC CIP, NAIC, CPNI & CPA ethics
Your InfrastructureAWS or Azure VPC — you control the environment
CA-Barred Attorney on Founding TeamCompliance depth built in, not contracted out

The Situation

The board wants AI.
The compliance team
keeps saying no.
Both are right.

Your leadership team is watching competitors adopt AI and closing the gap. The pressure is real and it's coming from the top.

Your compliance team isn't being obstructive. They're doing their job. Customer data, operational data, financial records, network topology — this information cannot legally or safely touch a third-party API. They know it. You know it. The cloud AI vendors are hoping nobody asks the question too loudly.

There's a harder problem underneath that one. Your team is probably already using AI. Underwriters summarizing loss runs in ChatGPT. Engineers feeding operational data into Copilot. Nobody officially approved it. Nobody officially knows. The gap between your formal policy and what's actually happening is exactly where regulatory exposure lives — and it shows up in audits.

The question isn't whether to adopt AI. The question is whether you do it on your terms, with a defensible compliance framework in place, before a regulatory review forces the conversation.

The Solution

Private AI built for industries
where the data can't leave the building.

Ark33 closes the gap between board pressure and compliance reality. We deploy enterprise-grade AI models on your own cloud infrastructure — your AWS or Azure environment, fully inside your perimeter. We fine-tune them to your domain. We wrap the deployment in a compliance framework designed to survive regulatory scrutiny.

Your team gets AI that performs. Your compliance team gets something they can actually say yes to. Your data never moves.

How It Works

Three phases. Your model running inside your walls.

Phase 01 — Assess
AI Readiness Assessment
$18,000 fixed fee · 3 weeks · Credits toward implementation

We audit your infrastructure, map your regulatory obligations, and identify where AI creates the most value with the least risk. Five deliverables: infrastructure audit, compliance gap analysis, model recommendation, use case prioritization map, and a fixed-price implementation proposal.

Phase 02 — Deploy
Private AI Implementation
$95,000 – $140,000 · Milestone-gated · ~12 weeks

An enterprise AI model — fine-tuned to your domain — deployed on your AWS or Azure VPC. Nothing leaves your perimeter. Governance dashboard, audit logs, and the compliance documentation your regulators will ask for are built in from day one.

Phase 03 — Run
Annual Platform License
$48,000 – $72,000 / year · 12-month commitment

Your model stays current. We handle model updates, security patches, compliance documentation refresh, and the quarterly audit package. You license the platform. We run the infrastructure. Your team uses the AI.

Why Ark33

Three things that rarely exist under one roof.

Legal & Compliance Depth — Built In, Not Bolted On

Brian is a CA-barred attorney who has worked inside the regulatory environments our clients navigate. The compliance framework isn't an add-on. It's the foundation the entire deployment is built on. When a state examiner asks about your AI governance program, you have a documented answer.

Enterprise Architecture That Runs in Your Environment

Rick has 25 years building enterprise technology organizations — including 150-engineer teams — and is hands-on with enterprise model deployment and private cloud architecture. The model runs on your infrastructure because that's the only architecture we build.

Fine-Tuned Models That Perform

We don't drop a generic model into your environment and call it done. We fine-tune it on your domain — your language, your workflows, your use cases. The model inside your perimeter performs better than what you'd get from any cloud API. Your data never trains anyone else's model.

$720K
Annual return on a 40% efficiency lift
for 20 relevant staff

A mid-market organization with 20 staff spending 30% of their time on automatable work is burning roughly $1.8M per year in addressable labor. A 40% efficiency improvement returns $720,000 annually.

The implementation investment is $95,000–$140,000. The payback period is 10–12 weeks.

The harder number: one regulatory finding tied to unauthorized AI use can exceed the entire implementation cost. Every week your team uses shadow AI without a compliance framework in place is a week that risk accrues.

Schedule a Risk Assessment →
Common Questions

The questions we hear on every discovery call.

We're not ready for a full implementation. +
That's exactly what the AI Readiness Assessment is for. Three weeks, five deliverables, a fixed $18,000 fee. You learn exactly where you stand, what your obligations are, and what a compliant deployment would look like. No commitment to implementation required — though 60% of clients who complete the Assessment proceed within 60 days.
Can't we just use a cloud AI vendor with a BAA in place? +
A Business Associate Agreement addresses data handling liability — it doesn't resolve the underlying regulatory exposure in your specific vertical. NERC CIP-011, NAIC model bulletin guidance, CPNI obligations, and CPA confidentiality ethics rules are not resolved by a vendor BAA. Brian can walk you through the specific exposure in your industry on a 20-minute call.
We don't have an internal AI team. +
You don't need one. That's the point of licensing the platform. We deploy, maintain, update, and document everything. Your team uses the AI. We run the infrastructure.
How is this different from building our own cloud AI setup? +
Most organizations that attempt this internally underestimate two things: the complexity of properly hardening a model deployment for regulated environments, and the compliance documentation burden. We've built the frameworks, the deployment architecture, and the governance layer specifically for mid-market regulated enterprises — you get the result without staffing a multi-person AI engineering and compliance team.
The Team

Built by people who've worked inside these industries.

Brian
Co-Founder

CA-barred attorney. 10+ years in telecom and utility operations. Built AI governance and compliance frameworks for regulated industries. When compliance teams ask hard questions about AI deployment, Brian has the answers — because he's spent a decade on their side of the table.

Rick
Co-Founder & CTO

25 years in enterprise technology leadership. Former CTO of organizations with 150+ engineers. Hands-on with enterprise model deployment and private cloud architecture. Builds the systems that never leave your perimeter.

Brandon
Co-Founder & CPO

Former entrepreneur. Full-stack product development. Designs the governance dashboards and audit interfaces your compliance team will actually use. Builds fast. Ships clean.

The First Step Costs Nothing

Book a 20-minute compliance risk assessment with Brian.

He'll ask five questions about your current situation and give you his honest read on your regulatory exposure — in plain language, no pitch. If there's a fit, you'll know. If there isn't, you'll still leave with a clearer picture of where you stand.

Schedule Your Compliance Risk Assessment →

brian@ark33.solutions