Private AI Server
A private AI server is hardware you own, configured to run open-source models locally. It provides a local processing environment for documents and workflows. Any connected external service or commercial-model routing is a separate data-handling choice to review in the scope.
Start with a free written recommendation on one workflow, reviewed by Christopher Myers and emailed within 24 hours. No call or purchase required. Prefer a live discussion? The free assessment is a 30-minute conversation.
Where this one earns its keep.
These industries commonly have this workflow. Fit depends on your volume, tools, exceptions, and the cost of the manual work; these links are examples of suitability, not a list of customer deployments.
What sending your data outside actually risks.
Start with your actual workload and costs. Treat the calculation as a way to test the opportunity, not a promise of revenue or savings.
What to count. hours a month your team spends on work they will not put through a public tool × loaded hourly cost. Use gross profit rather than total revenue when valuing recovered business. Subtract software, maintenance, and human review costs, and avoid counting the same saved time twice.
The ROI calculator models the same shape across a whole team, and its assumptions are published in full underneath it. The number that actually matters comes out of an AI Readiness Audit, which measures your workflows instead of averaging them.
Choose the boundary before the hardware.
A local server is one part of a private workflow. The scope also needs to cover connected services, access, backups, maintenance, and what happens when the model cannot complete a task.
List the permitted processing routes
Identify the documents, model inputs, outputs, logs, and backups involved. For a local-only workflow, verify that connected components do not introduce an external processing route. For a hybrid workflow, define which tasks and information may use external services.
Test the intended work
Use representative documents and expected outputs to assess quality, response time, and concurrent use on the proposed hardware. A hardware specification alone cannot establish that a model will meet your workflow requirements. Keep a path to a person when the approved system cannot answer.
Price ownership and operation together
Include the hardware, configuration, integrations, backups, replacement planning, and the person responsible for updates. A hybrid arrangement also needs external usage and subscription costs. The written quote should distinguish included work from recurring expenses.
Plan maintenance and recovery
Agree who applies updates, how changes are tested, how access is removed, and how a failed system is restored. A model change should be checked against the workflow’s acceptance examples before the team depends on it.
Compare local and hybrid AI · Read the documented data controls · Review ongoing cost categories
Discover, build, evolve.
Define the operating boundary before choosing a model or a tool. Your written scope connects the workflow to the systems, decisions, and people it depends on.
Discover. Start with a free workflow plan for an initial written recommendation based on what you share. Use an AI Readiness Audit when the workflow, tools, and exceptions need deeper investigation, or discuss direct sprint scoping if the work is already defined.
Build. Agree the scope and fixed quote before work begins. Define routine actions that may run automatically, decisions requiring human approval, and the tests the workflow must pass.
Evolve. Once it is live it needs watching: what it handles, what it escalates, what changed in your business since. That is Managed Services, and it is optional.
Delivered through AI Implementation Sprint.
The range below is for the delivering service, not a per-feature price. Your quote identifies the capabilities, integrations, and operating requirements included in the engagement.
An AI Readiness Audit runs $3,500–$8,500 and tells you whether this build is the right first move. This capability is delivered through AI Implementation Sprint; several related capabilities may share one scoped engagement. $18,000–$60,000, quoted fixed in writing before work begins.
Private AI Server, asked plainly.
01Do we own the hardware?
Yes. It is bought in your name and it is your property, not a leased seat. That is the difference between this and every subscription alternative.
02What happens if you stop working with us?
The machine stays where it is and keeps running. You own the hardware and the models on it are open-source, so nothing switches off when an engagement ends.
03Is a local model good enough?
It depends on the task, model, hardware, and quality requirements. We test the intended workflow. If external reasoning is appropriate, the scope explains what filtered information may leave and which controls apply.
04What does it cost?
It is delivered through an AI Implementation Sprint, quoted fixed in writing before work begins. Hardware is quoted as part of that scope, not billed as a surprise afterwards.
One workflow. A written first step.
Describe the task and the tools involved. Christopher Myers reviews your free workflow plan, emailed within 24 hours, with an initial recommendation on where to start and what needs scoping. No call or purchase required. The plan is not a paid audit or a fixed implementation quote.
Prefer to talk it through? Book a free 30-minute assessment for a live discussion of fit and next steps.