# Private AI engineering, in a controlled environment

> AI-assisted software delivery on privately hosted models: model evaluation, infrastructure setup, access boundaries, expert build, QA and optional ongoing management.

Source: https://npcoding.ca/services/private-ai-engineering/

AI-powered software delivery in a controlled processing environment. We set up and evaluate privately hosted models, agree the access boundaries, and build your software with the same design, QA and release discipline as every NPCoding project, with optional ongoing management of the models and infrastructure.

Development package (how we build with AI). It applies across the four capabilities: [Software & App Development](https://npcoding.ca/services/ai-software-engineering/), [QA & Release Assurance](https://npcoding.ca/services/qa-testing/), [DevOps & Managed Operations](https://npcoding.ca/services/devops-managed-operations/), [Product Design & UI/UX](https://npcoding.ca/services/product-design-ux/).

## Overview

Some projects call for AI-assisted development on infrastructure the client controls: regulated data, contractual restrictions or an internal policy. This package brings our full engineering practice into that environment.

We clarify the requirements, select and evaluate privately hosted models on your actual tasks, and set up the infrastructure with agreed access boundaries. Then we deliver the work: engineering, UI/UX, QA and controlled releases, reviewed by the same senior people as any other project.

It's a tailored engineering engagement, not hardware rental: the value is in choosing, configuring and operating the environment well. After launch, we can keep managing the models and infrastructure as an ongoing service.

## Is this the right service?

Choose Private / Local AI Engineering when:

- We're building or changing your software, and AI processing must stay on infrastructure you control
- Contracts, regulation or internal policy rule out third-party AI processing of your code or data
- You want the environment set up for the project, and optionally managed afterwards

Consider instead:

- [Private AI Infrastructure](https://npcoding.ca/services/private-ai-infrastructure/) when you need the private model environment itself, for your own team, without a development project
- [Claude Code & Codex Engineering](https://npcoding.ca/services/claude-code-codex-engineering/) when approved cloud AI tools fit your policies

## What's included in private / local AI

- **Requirements & feasibility:** Clarify what must stay private, why, and which parts of the work it applies to.
- **Model selection & evaluation:** Open-weight models compared on your tasks for capability, speed and cost, so the trade-offs are known before you commit.
- **Infrastructure setup:** Hosting in your environment or cloud account, configured for the workload, with logging and monitoring.
- **Access boundaries:** Network rules, permissions and audit logging, agreed and documented with you.
- **Expert delivery:** Engineering, UI/UX and QA carried out in the private environment, with every change reviewed.
- **Release & ongoing management:** Controlled releases with rollback, plus optional ongoing management of the models and infrastructure.

**Need only the private model infrastructure?** If your own team will use the environment and no software needs building, Private AI Infrastructure covers the design, setup, evaluation and operation on its own.

## What you receive. Who is responsible.

- **Environment design:** A documented design of where the models run, who can access them and what connects to them.
- **Model evaluation:** Results from testing candidate models on representative tasks, with a recommendation.
- **A working environment:** The private AI environment, set up and tested, then handed over or managed by us.
- **Delivered software:** Your software, built, reviewed, tested and released by NPCoding engineers, designers and QA.

## How NPCoding delivers it

1. **Clarify requirements:** Establish what must stay private, under which agreements, and for which parts of the project.
2. **Evaluate models:** Compare candidate models, hardware and hosting on representative tasks, and agree the trade-offs.
3. **Set up the environment:** Build the environment with documented access boundaries, logging and monitoring.
4. **Build, review & test:** Engineers, designers and QA deliver the work inside the environment, with every change reviewed.
5. **Release & manage:** Release under change control, then patch, monitor and update models as agreed.

## How we build: expert engineers, the best AI harness

Every project is built by NPCoding's engineers in a proven AI engineering harness, then reviewed, tested and released by people. Two development packages decide where the AI runs while we build: leading cloud tools or privately hosted models. Both apply across all four capabilities, with the same engineering, UI/UX, QA and DevOps standards.

### Private / Local AI Engineering

*AI-powered software delivery in a controlled processing environment.*

For projects with specific processing requirements. We set up and evaluate privately hosted models, agree the access boundaries, then design, build, test and release your software inside that environment.

- A senior engineer as your HR for AI, managing the agents
- Privately hosted models, evaluated on your own tasks
- Infrastructure setup with agreed access boundaries
- Expert engineering, UI/UX and QA
- Controlled releases with review and rollback
- Optional ongoing management of the private models and infrastructure.

Details: https://npcoding.ca/services/private-ai-engineering/ · Plan a private AI project: https://npcoding.ca/contact/?topic=build&package=private#enquiry

### Claude Code & Codex Engineering

*AI-accelerated delivery with Claude Code and OpenAI Codex, directed by experienced engineers.*

Our engineers use Claude Code and OpenAI Codex for analysis, implementation, refactoring, testing and documentation, choosing the right tool for each task. We run the workflow and take responsibility for delivery, so you never manage coding agents yourself.

- A senior engineer as your HR for AI, managing the agents
- AI-assisted codebase analysis and planning
- Implementation and refactoring, reviewed by engineers
- Tests and documentation with every change
- Architecture, UI/UX, QA and DevOps behind each release
- Continued development, maintenance, QA and operations, as scoped.

Details: https://npcoding.ca/services/claude-code-codex-engineering/ · Plan a Claude Code & Codex project: https://npcoding.ca/contact/?topic=build&package=claude-codex#enquiry

### Compared

- **Suitable requirements:** Private / Local AI: Projects whose contracts, regulation or internal policy call for AI processing on controlled infrastructure. Claude Code & Codex: New builds, modernization and ongoing development where approved cloud AI tools fit your policies.
- **AI processing environment:** Private / Local AI: Open-weight models hosted privately, on infrastructure you control or that we set up for the project. Claude Code & Codex: Claude Code and OpenAI Codex, processed by each provider under the account and settings approved for your project.
- **Setup and infrastructure:** Private / Local AI: Model selection and evaluation, hosting and access setup, scoped before development starts. Claude Code & Codex: No AI infrastructure to build: we bring an established, reviewed workflow into your repositories.
- **Data and access arrangements:** Private / Local AI: Access boundaries, logging and network rules agreed and documented with you. Claude Code & Codex: Access limited to the repositories and data the work needs; provider terms and settings confirmed with you.
- **Expert oversight:** The same in both: a senior engineer acts as HR for AI, directing and reviewing all AI-assisted work, and designers, QA and DevOps own their parts of every release.
- **Ongoing management:** Private / Local AI: Maintenance, QA and operations as scoped, plus optional management of the private models and infrastructure. Claude Code & Codex: Continued development, maintenance, QA and operations, as scoped.

The package decides where AI processing happens while we build. Where your finished application runs is planned separately, in your cloud account or another environment agreed for the project.

## Why NPCoding

- **Processing you control:** Know where models run, who can access them and what data they see.
- **Honest trade-offs:** Capability, speed and cost are measured on your work before you commit.
- **The same standards:** Engineering review, UI/UX, QA and release controls match every other NPCoding project.

## Tools and technologies

Open-weight models, Self-hosted inference servers, GPU infrastructure, Private networking, Docker, Linux, Access & audit logging, Evaluation suites

## Industries

- [Healthcare](https://npcoding.ca/industries/healthcare/)
- [Finance](https://npcoding.ca/industries/finance/)
- [Education](https://npcoding.ca/industries/education/)
- [Manufacturing](https://npcoding.ca/industries/manufacturing/)

## Frequently asked questions

### When does a private AI environment make sense?

When contracts, regulation or internal policy rule out processing your code or data with third-party AI services, even under business terms. For many projects, approved cloud tools with the right account and settings are enough. We'll help you work out which applies.

### Is a private environment automatically more secure?

Not automatically. It changes who controls the processing and the infrastructure. Security still depends on access control, patching, monitoring and how the whole system is operated, which is why those are part of the package.

### Does private mean total isolation, or that our data stays in Canada?

Only if the architecture is designed that way. We document where each component runs, who can access it and what it connects to. Isolation and data residency are established by that architecture and your agreements, not assumed, so we confirm them for each project.

### Will a private model be as capable as Claude Code or Codex?

Often not on complex work, and it may be slower. Privately hosted models can work very well for well-defined tasks. We evaluate candidates on your actual work before you commit, so the trade-off is clear.

### Is this a GPU rental service?

No. It's an engineering engagement: we scope, set up and evaluate the environment, build your software with it and, if you choose, manage it afterwards. The hardware can run in your own environment or cloud account.

### Can you manage the models and infrastructure after launch?

Yes, as an optional ongoing service: monitoring, patching, controlled model updates and access reviews, with responsibilities agreed per engagement.

### If an AI coding tool runs on our machines, does the AI run there too?

Not necessarily. Many AI coding tools run locally but send prompts and code to a cloud model for processing. Private processing requires the model itself to run on infrastructure you control, which is what this package sets up.

### Does private hosting make us compliant?

No single technical choice does. Private hosting gives you more control over processing, which can support your privacy and contractual obligations. Compliance also depends on your policies, your agreements and how the whole system is operated, so we work alongside your legal and privacy advisors.

### If AI stays on private infrastructure, must our application be self-hosted too?

No. Private / Local AI Engineering is about where AI processing happens while we build. The finished application can run in your cloud account, on your own servers or in another environment agreed for the project; production hosting is planned separately.

Plan a private AI project: https://npcoding.ca/contact/?topic=build&package=private#enquiry

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NPCoding · AI-powered software & app development · Toronto, Canada · support@npcoding.com · https://npcoding.ca/contact/