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Discuss your AI project

Nirox Labs · Dependable custom AI · Hull, UK

Dependable custom AI, built around your business.

Applications, knowledge assistants and agents that work from your own information, show their sources and wait for approval where it matters. You work directly with the founder who scopes, builds and hands over your system.

Free first call · Fixed price after scoping · Sometimes the answer is a simpler tool

Liam Silk, founder of Nirox Labs

Liam Silk · Founder · Nirox Labs · Hull

You speak to the person who scopes, builds and hands over your system. 10+ years of professional experience in software engineering.

What I build

Your business has its own way. Your AI should too.

Nirox Labs builds custom AI for established businesses across the UK, from a base in Hull. It helps when the information is scattered, the process is specific or the product you need doesn’t exist off the shelf.

  1. 01

    Custom AI applications

    01 / Built for your business

    An internal tool, a client portal or an AI feature inside your product. Software designed around the job your business needs to do.

    Your workflow. Your interface. Your system.

  2. 02

    Knowledge assistants

    02 / Built for your business

    Give your team a useful answer from your own documents, with the source attached. Build company knowledge into the tools people use.

    Company documents → answers with sources

  3. 03

    AI agents

    03 / Built for your business

    Read an enquiry, check a record, prepare the next step. Connect reasoning to actions across your systems, with limits and approvals built in.

    Context → a decision → a controlled action

Before you build

Start with a better question.

Where could AI make a meaningful difference? I help you assess the opportunity, compare an existing tool with a custom build and define a sensible first version. Automation is one option; the business outcome decides.

Explore AI consultancy

From a business question to a working system

Illustrative interface and data. Not a client system.

Example 01 · Knowledge assistants

The answer comes with its source.

A team member asks a question. The assistant searches the documents they are allowed to use, returns a grounded answer and points back to the relevant source.

Explore knowledge assistants Illustrative interface and data. Not a client system.
nirox labs / workspace Example
Request

What information do we need before a project starts?

Approved company knowledge Project onboarding handbook Current version · access checked Source record connected
  1. Check document permissions
  2. Retrieve the relevant guidance
  3. Prepare an answer from the source
  4. Attach the source and flag gaps
Result Ready when you are.

If the source is missing or unclear, the assistant says so.

Illustrative interface and data. Not a client system.

When custom AI makes sense

When custom AI makes sense. And when it doesn’t.

If an existing product does the job, I’ll tell you.

Your knowledge is hard to use.

Answers are buried in documents or depend on a few experienced people. Give teams a way to find the right information and check where it came from.

Your process has outgrown the software.

People bridge the gaps between systems, interpreting documents and handling exceptions. Build around those decisions and connections.

Your product could do more.

Help customers find a suitable option, work through information or complete a specialist task. Add AI inside the experience they already use.

From idea to everyday use

Map. Shadow. Own.

A focused first version. Tested in the real world. A clear path to what comes next.

  1. 01

    Map.

    A problem worth solving.

    We work through the outcome, your data and the systems involved. You get a focused scope, success measures and an agreed price before the build.

    • Business outcome
    • Feasibility & constraints
    • A costed first version
  2. 02

    Shadow.

    Evidence before dependence.

    I build and test against real examples. Where the system takes action, it runs alongside your existing process first. Your team reviews outputs and exceptions.

    • Build & integrate
    • Test against real work
    • Agree what is ready
  3. 03

    Own.

    Your system. A clear way forward.

    I deploy the agreed system, document it and hand it over. I define running costs and responsibilities, with ongoing engineering available as your needs grow.

    • Deployment & documentation
    • Team handover
    • Support agreed with you

How a build is made dependable

Mapwhat we agree
Shadowwhat you see before it acts
Ownwhat you keep
  • The outcome and how success is judged
  • The data and systems involved
  • A written scope
  • A fixed price before the build
  • Running costs estimated separately
  • Built and tested on your real examples
  • Answers show their sources
  • Anything that takes actions runs alongside your current process first
  • Approval points and an audit trail agreed with you
  • Deployment in the agreed environment
  • Documentation
  • Team training and handover
  • Source code for the custom work
  • Running costs and responsibilities defined
  • Optional ongoing engineering

Need engineering beyond the first project? Work with an AI engineer on an ongoing basis

The person behind Nirox Labs

Liam Silk. Your engineer.

You work directly with the person scoping and building your system. Liam founded Nirox Labs and brings more than ten years’ experience across software engineering, training and helping businesses of all kinds adopt new ways of working. His focus now is AI engineering and solution design.

That training background is why documentation, team training and a proper handover come with every project. Based in Hull, working with businesses across Yorkshire and the UK.

More about Liam
Role
Founder, Nirox Labs
Experience
10+ years’ professional experience
You work with
The person scoping and building your system
Based
Hull, UK
Working
Across Yorkshire & the UK

Inside Nirox Labs / an internal build

Putting my own knowledge to work.

Liam’s account of building an internal AI operating system with Claude Code: bringing business context, working methods and reusable instructions into one place.

Read the engineering story An internal Nirox Labs project, not a client case study.

Before we start

Good questions. Straight answers.

A clearer idea of what you’re buying.

Discuss your AI project
What does Nirox Labs build?

Nirox Labs designs and builds custom AI applications, company knowledge assistants and AI agents. That can mean an internal document-review tool, an assistant that answers from your own information, or an AI feature connected to your existing software. It is based in Hull and works with businesses across the UK.

How is custom AI different from workflow automation?

Workflow automation follows defined rules. Custom AI can interpret language and documents, retrieve relevant knowledge or choose between permitted next steps. An application may use both. I choose the simplest approach that meets the requirement; not every process needs AI.

Should we buy an existing tool or build something custom?

If an existing product solves the problem well, that may be the better starting point. A custom build becomes useful when your process, data, integrations or customer experience need something more specific. I assess that fit before proposing a build.

Do we need a technical brief?

No. Bring the outcome you want, an example of the work and the systems involved. I help establish feasibility and define a first version. If the uncertainty needs deeper investigation, we agree a separate discovery scope before committing to the build.

What does a custom AI project cost?

The price depends on the application, available data, integrations and testing required. After scoping, we agree a fixed price for the defined work. Hosting, model usage, third-party licences and optional ongoing support are discussed separately, so you can assess the cost of running the system as well as building it.

How do you handle accuracy and access to our data?

We agree who can access which information, which actions require approval and how uncertain results should be handled. I test realistic examples and exceptions before release. Hosting, model providers, data handling and monitoring are project decisions, discussed during discovery.

Who owns the system, and can you support it?

You own the custom work I build for you, with documentation and a handover. Third-party tools retain their own licences and fees. Ongoing engineering and support can be scoped separately, with response expectations and responsibilities agreed in advance.

You’re one person. What if something breaks?

That is a fair question, and it shapes how I work. I document what I build, hand it over with training so your team can run it, and agree support expectations and responsibilities in writing before launch. Where a system matters to daily operations, ongoing engineering can be scoped separately. If something needs more than one pair of hands, I say so up front.

How do you test an AI system before we rely on it?

I build a set of real questions or tasks from your own work, with the expected source or outcome for each, then run the system against them before anyone depends on it. Anything that takes action runs alongside your current process first. Where the system is unsure, it should say so rather than guess. Read the free RAG guide for the question-set method.

A useful first conversation

Leave with decisions, not a slide deck.

Free first call · Fixed price after scoping

Bring the problem, the process or the idea. I’ll tell you what’s possible, where the risks are and whether a simpler tool would do.

Discuss your AI project Read the free RAG guide Or email hello@niroxai.com

Independent AI engineering. Based in Hull & East Yorkshire, working across Yorkshire and the UK.

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