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AI consulting & assistants

Make AI useful inside your business, one practical job at a time.

Where AI is genuinely useful in a small business.

A general chatbot is easy to try. Making it useful in your business takes more thought: what information can it use, which decisions can it make, and how will anyone know whether its answer is right?

We start with a specific job: finding an approved procedure, preparing a draft, summarizing project information, or assembling a daily brief. Then we define the source material, permissions, review steps, and a small set of examples that show whether the assistant is doing useful work.

WHAT A PROJECT CAN INCLUDE

A focused AI use case

Choose a task with a clear owner, a useful output, and a realistic way to check quality.

Business knowledge organization

Structure the procedures, reference material, and project context an assistant needs to answer reliably.

An assistant your team can use

Connect the agreed tools, make uncertainty visible, and keep consequential actions under human control.

What this can look like.

A team member asks how to handle an unusual customer request. An internal assistant finds the relevant procedure, points to its source, and prepares a response for review. It does not invent company policy or promise an exception.

A good fit

Best for repeated language and knowledge tasks where a person can review the output. A simple automation may be better when the rules are already clear.

Agree on what success means.

Choose a baseline and useful measures before the build.

  • Accuracy against agreed example tasks
  • Time required to review an answer
  • Unsupported answers or missing sources
  • Useful tasks completed with appropriate review

What it costs.

$1,500 to $8,000

A single focused use case sits at the lower end. An internal assistant with real business knowledge behind it sits at the upper end.

Published so you can decide whether to call, not as a quote. Every project is priced after a conversation about the actual work, and these ranges are reviewed as costs change. If your project sits outside them I will say so early rather than late.

How long it takes.

Three to six weeks. The build is fast; organising the knowledge it reads is the long part, and skipping that is why most of these fail.

What the first weeks look like.

  1. 01

    Week one, pick one job. One task with a clear owner, a useful output and an obvious way to tell whether it did well. Not 'an AI for the business'.

  2. 02

    Weeks two and three, the source material. Gathering and structuring what it needs to read. This is unglamorous and it is the whole difference between an assistant that is useful and one that is confidently wrong.

  3. 03

    Weeks four onward, examples and boundaries. A set of real cases with the right answers, including the cases where the correct response is to ask a person. This is what you test against later.

What this is built with.

  • A current-generation model, chosen per task rather than by brand loyalty
  • Your existing documents, procedures and records as the source material
  • A retrieval layer so answers come from your material rather than from the model's imagination
  • A review step wherever a wrong answer would be expensive

Named so you can check the running costs yourself. Anything with a subscription is bought in your name, on your card, so the tools stay yours whatever happens between us.

What usually goes wrong.

It answers from nowhere

If it cannot point at the source, you cannot trust the answer, and a plausible wrong answer is more dangerous than an obvious one.

Nobody owns the material

Procedures change. If nothing updates what it reads, it quietly becomes an expert on last year.

It was pointed at a task that never needed it

Plenty of work is a rule, not a judgement. Adding a model to a deterministic task adds cost and uncertainty and improves nothing.

What I will not do.

  • Letting it make a consequential decision unreviewed.
  • Feeding it material you have not agreed can be used.
  • Selling you an assistant when a form and a rule would do.

A clear process, first conversation to handoff.

  1. 01

    Talk it through

    Show me the task, the tools involved, and where things get held up.

  2. 02

    Agree on the work

    We define the scope, cost, and what the finished system needs to do.

  3. 03

    Build it. Try it.

    We test it with real tasks, including the awkward cases that come up.

  4. 04

    Put it to work

    You get a walkthrough, documentation, and an agreed plan for support.

AI consulting questions, answered without the hype.

Can an assistant work with our documents?

That depends on the format, permissions, and systems involved. We review a small, approved set first and design access around the task.

Will the AI run my whole business?

We build bounded systems for specific work. Approvals, ownership, and a way to recover from mistakes remain part of the process.

Can you help us decide what to build?

Yes. An initial review can identify a useful starting point and the information needed to scope it. You do not need a technical specification to start.

Related work.

Workflow automation

Connect inquiries, follow-ups, handoffs, and everyday admin across the tools you already use. Business automation, workflow automation, same job.

AI receptionist & answering

A phone line that picks up, takes the details, and hands you a job you can actually call back.

Missed call calculator

Work out what the calls you cannot answer are costing, on your own three numbers.

See every service, or the industries this work is built for.

Based in Houston. Working across the Houston metro.

For small businesses in Houston, Katy, Cypress, Sugar Land, Pearland and The Woodlands.

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