Use AI Without Handing
Your Data to Someone Else.
Your team could save hours with AI, but the documents involve customers, contracts or health and financial details, so the answer has been no. Private AI means the model runs where you control it: in your own cloud account or on hardware you own, with access and logging you decide. We design and deploy it, and tell you plainly when a standard provider would serve you just as well.
Signs This Applies to You
AI is banned at work
Staff are told not to paste business information into public AI tools, so they either do not use AI or use it quietly.
Contracts ask where data goes
Customers or partners require you to say exactly where their information is processed and stored.
Manual redaction
Someone strips names and numbers out of documents before anyone is allowed to use an AI tool on them.
Regulated information
The work involves financial, health, legal or personnel records with rules about who may see them.
Unpredictable usage bills
Per-request pricing makes a high-volume use case hard to budget.
Dependence on one vendor
You are uneasy that a single provider’s price change or policy change could stop a process you rely on.
What It Actually Costs
The cost of not using AI rarely shows up anywhere, and neither do the hours spent redacting or working around the restriction. This illustration counts only those hours.
- 1 person
- doing the work
- 30 minutes
- each time
- 20 times a week
- across everyone
- $50 an hour
- loaded cost per person
About 10 hours a week, or $23,000 to $26,000 a year
What Private AI Actually Involves
"Private" can mean several different things. The first job is agreeing which one your data needs, because the cost and capability differ a great deal.
Classify the data and the rules
We identify what information is involved, who may see it and what your contracts or regulations require, before choosing any technology.
Choose where the model runs
Options range from a managed model inside your own cloud account to an open-weight model on your own servers. Each trades capability, cost and control differently.
Prove it on your work
We test the chosen model against real tasks. Smaller private models can be less capable than the largest public ones, and you see that difference before committing.
Lock it down and hand over
Access control, logging and data retention are set up in your accounts. You get documentation and the ability to replace the model later.
Before and After
An illustration of a common workflow, not a client project.
An insurance agency forbids staff from using AI tools with client files. Summarizing a policy file before a renewal call takes an agent half an hour of reading.
A model running inside the agency’s own cloud account summarizes the file and lists the coverage questions to raise. Only licensed staff can use it, every request is logged, and client files never go to a public AI service.
Private Deployment, or a Standard Provider?
Private deployment makes sense
- Contracts or regulations restrict where data is processed
- Volume is high and steady enough to justify fixed infrastructure
- You need full control over logging and retention
- Losing access to one vendor would stop a critical process
A standard provider is probably fine
- A provider’s business data terms already satisfy your requirements
- Usage is light or occasional
- The task needs the most capable model available
- Nobody can operate or pay for the infrastructure over time
Typical Starting Points
Work is priced by scope, not by the hour. You get a written scope with a fixed price before anything starts, and larger builds are split into milestones. The ranges below show where engagements typically start.
See Starting Prices
| Engagement | When it fits | Investment |
|---|---|---|
| Automation Opportunity Review | You know the workflow hurts, but not yet what, if anything, to build: one workflow reviewed, with the smallest worthwhile fix in a written action plan. | $495 fixed fee |
| Custom Engagements | New products, AI agents, private AI, custom applications, modernization and data platforms, scoped and priced in writing. | Quoted in writing |
| Operations Automation Partnership | After a build: monitoring, maintenance, vendor and API changes, and small improvements. | From $750 / month |
Hosting, domains, licenses, subscriptions, and processing fees stay in accounts you own and are billed to you directly by each vendor whenever practical. Where we must place an approved charge on your behalf, that amount is collected before we incur it.
After the Build
Every build ends with documentation and a handoff, so your team can run it. If you would rather not, a monthly partnership covers monitoring, vendor and API changes, and small improvements under its own written agreement.
See Partnership LevelsBefore You Ask
- What does private AI actually mean?
- It means the model runs somewhere you control, such as your own cloud account or your own hardware, so your data is not processed by a public AI service. How strict that needs to be depends on your data and obligations.
- Is a private model as good as the big public ones?
- Often not for the hardest tasks, and sometimes more than enough for focused ones like summarizing or extraction. We test on your real work so you can judge the difference before paying for a deployment.
- Do we need to buy servers?
- Not necessarily. Many private deployments run in a cloud account you own. Your own hardware makes sense when volume is high or data must stay on premises.
- Does this make us compliant?
- No technology makes a business compliant on its own, and we do not provide legal or compliance advice. We build to the requirements you and your advisors define and document how the system handles data.
- Can we switch models later?
- Yes. The application is built so the model underneath can be replaced without rebuilding everything around it.
Figures on this page are illustrations based on the stated inputs, not client results, and are not a promise of savings. We do not guarantee any particular business, time-saving or technical outcome. This page is a summary for convenience; our Terms of Service govern.
Full terms: Terms of Service
What Would You Use AI For If Your Data Could Stay Put?
Tell us the task, the kind of information involved and any rules you must follow. We will tell you which kind of private deployment, if any, it needs.