Transparency, not hype
No black boxes. No vague promises about "enterprise-grade AI." Just a documented process, real pricing, and a Vermont operator who's been doing this kind of trusted infrastructure work for two decades.
Book a 30-Min Readiness Call →Tim Parrow · Founder
Founder, Vermont AI Systems
Tim spent two decades building and running Vermont MSPs — Pine Computers and Prosystem Technology — as the trusted IT infrastructure partner for regional businesses. Law firms, manufacturers, healthcare practices, financial advisors: he's seen their data environments up close, managed their compliance requirements, and earned their trust one server room at a time.
Vermont AI Systems isn't a Bay Area AI shop that bolted on enterprise sales and a compliance checkbox. It's the same trust model Tim spent 20 years building — now applied to AI. When your AI runs on infrastructure we built, you're not handing your data to a startup. You're working with the person who's been your region's infrastructure partner for decades.
"The businesses that trust us with their AI are the same kinds of businesses I've been supporting since the early 2000s. The technology changed. The responsibility didn't."
— Tim Parrow, FounderVermont-based. We serve businesses across the US.
Responses within one business day. For a structured conversation, book a readiness call or schedule a free AI Privacy Audit.
Every engagement follows the same four phases. The scope is fixed per phase. The deliverables are written down before we start. No surprises at invoice time.
Before we write a line of code, we need to understand what you actually have. This phase is an audit — of your data assets, your business processes, your existing tools, and your risk exposure.
The Assessment fee applies as a full credit toward any subsequent build engagement.
We build a working private model against your highest-value use case from the Assessment. This is where we validate the approach before committing to a full production build.
The full deployment — production-grade infrastructure, all integrations, staff training, and 90 days of post-launch support included. By this phase, we've already validated the model works. Now we build it to run your business.
Your business changes. Your AI should too. The retainer keeps your model current, your team supported, and your compliance position documented as regulations evolve.
If you cancel the retainer, you keep the model. No vendor lock-in — we built it to be yours.
The diagram below shows the data flow for a typical Vermont AI Systems deployment. Every boundary is labeled. Every data movement is accounted for. Nothing goes to a public LLM API.
Your AI runs on infrastructure you control. Never co-tenanted.
Your training data and queries never touch OpenAI, Anthropic, or Google.
We produce a full data flow map you can hand to your compliance team.
These are the questions we get every time. Answered plainly, not in legal boilerplate.
In your environment. We deploy the AI to infrastructure you control — either your own on-premise servers, a private cloud environment (AWS VPC, Azure private, GCP private), or a dedicated hosted environment we configure and transfer to you. Your data does not sit on shared infrastructure. It does not sit on our infrastructure. After project close, we retain no copies.
No. We use open-weight base models — Llama, Mistral, Phi, and similar — which we fine-tune on your data locally. No step in our training or inference pipeline calls a public LLM API. Your documents, prompts, and outputs never leave your environment. This is the foundational design decision of every engagement we run.
Yes. The default for most engagements is either on-premise deployment (your servers, your building) or a private VPC you control. We can also set up a dedicated cloud environment that is entirely yours — single-tenant, no shared compute. After we complete the build and training, you have everything you need to run the system without us: model weights, configs, deployment scripts, documentation.
It's yours to keep. The trained model weights, the fine-tuning dataset, the deployment configuration, and all custom integrations transfer to you at project close. This is work-for-hire — you own the IP. If you end the retainer, you keep running your own AI. We retain no copies, no licensing claim, and no ability to shut down your system. There is no vendor lock-in because we built it to be yours from day one.
We classify every data type before training begins as part of the Readiness Assessment. Privileged legal data, PHI, and PII are handled with explicit controls: role-based access, audit logging, and in some cases data masking or pseudonymization in the training set depending on your compliance requirements. Our infrastructure designs are built with HIPAA and SOC 2 Type II in mind. We document every data flow and can provide those documents to your compliance team or auditors. We're not your compliance officer — but we design systems that make their job easier.
During the build, your Vermont AI Systems engineering team has scoped, time-limited access to complete the project. Access is documented and revoked at project close. Under the retainer, any ongoing support access is explicit: you grant it, it's time-bounded, and every session is logged. You can revoke access at any time. After the project ends, the only people who have access to your AI are the people you authorize.
That's part of what the Operations Retainer covers. Regulations change — HIPAA guidance updates, state privacy laws evolve, your industry adds requirements. Retainer clients get quarterly compliance documentation reviews and updated data flow maps. If a major regulatory change requires architectural changes to the AI system, we scope that as a change order and discuss it with you before touching anything.
Every phase has defined deliverables. Here's what three of them look like — using generic sample data, no client names.
A 15–20 page written report covering your data inventory, quality ratings, compliance flags, and AI opportunity ranking. Delivered before any contract for Phase 2 is signed.
Objective quality scoring against real prompts your team will use. Includes failure mode analysis and a go/no-go recommendation for production build. No vague "98% accuracy" claims.
A monthly report showing usage metrics, uptime, security audit results, and upcoming maintenance. So you know exactly what you're getting for $3,500/mo.
The readiness call is 30 minutes. Tim will tell you plainly whether private AI makes sense for your situation, what it would cost, and what the first phase looks like. No pitch deck. No commitment. If it's not the right fit, he'll say so.