06AI & transformation · AI consulting

AI consulting and AI transformation.

AI consulting answers three questions for a company: where would AI actually help, are we ready for it, and in what order should we do it?

We build it to order, around the way you work, or extend and connect the one you already have.

Fig. 00Which way first
Fig. 01Scattered, before it is joined

01What it is

In plain words.

AI consulting answers three questions for a company: where would AI actually help, are we ready for it, and in what order should we do it?

Most companies feel they should be doing something about AI and are unsure what. They are offered tools by every supplier, pilots that never reach production, and strategies that describe the future without saying what to do on Monday.

Useful advice is concrete. It looks at the work the company does, finds the places where reading, matching, predicting or drafting takes people's time, checks whether the data and systems can support a solution, and sets out a short list in order of value and difficulty. Then it gets built.

02What it includes

Every part, explained.

7 parts. Each can be built by itself; together they are one system.
Fig. 02Which way first

01

AI strategy

What AI is for in this business, in plain terms: the outcomes wanted, the problems worth solving, what to build, buy or leave alone, and how it will be governed.

02

AI readiness assessment

An honest look at the starting point: the state of the data, the systems it lives in, the skills in the team, security and regulatory limits, and what must be fixed first.

03

Process identification for AI

Walking through how work is really done to find the steps where a model would save time or catch errors, and equally the steps where it would not.

04

AI implementation

Building the chosen solution to production standard: measured on your data, integrated with your systems, monitored in use and handed over with the means to maintain it.

05

Enterprise AI integration

Fitting AI into the systems people already use, such as the ERP, the CRM and the service desk, so it appears in the workflow and not as one more tab.

06

AI automation strategy

Deciding which decisions a system may take alone, which it should recommend and which stay with people, and how each is checked.

07

Custom AI solutions

A system built for a problem no product addresses, on the same intelligence layer and principles as our own products.

Buy, extend or build?

A general strategy firm is a reasonable choice for board-level framing. Choose an engineering company when you want a plan that will be built by the people who wrote it, with the first stage scoped and priced. The formal version of this work is our AI audit: readiness, risks, opportunities and a roadmap, in writing.

Where intelligence fits

Advice about AI should itself be testable. Where we recommend a use, we say what would have to be true of your data for it to work and how we would measure it in a first stage. Where the evidence says a use is not worth doing, the report says that too.

Fig. 04From brief to hand-over

04How we build it

Five steps, in the open.

  1. 01

    Listen

    You describe the work and where it hurts. We look at the systems and the data you have now.

  2. 02

    Specify

    A written specification: what the system does, what it does not, what it connects to and how we will know it works. A clear quote before any work starts.

  3. 03

    Build in stages

    A working piece at each stage, on real data, so you steer early. The part that matters most comes first.

  4. 04

    Move the data

    Existing records mapped, cleaned of duplicates and reconciled against the old system before anything is switched off.

  5. 05

    Hand over

    Training, documentation and the keys. Your team can run it, and we keep it working for as long as you want us to.

One set of records underneath

Customers, products, suppliers, people and stock are each defined once. A second system joins the first; it does not start a competing copy.

Runs where you decide

Your own servers, a private cloud or a cloud account that belongs to you. Customer, employee and financial data stays on infrastructure you control.

Yours to keep

You own the code, the data, the configuration and the documentation. There is no licence fee to us and nothing stopping another team from taking it on.

05Questions

Before you ask.

Fig. 05What people ask first

Questions about AI consulting

What does an AI readiness assessment cover?

Data, systems, people and rules. Whether the data needed exists and is clean enough, whether your systems can supply and receive it, whether the team can run what is built, and which security and regulatory limits apply.

How do we find the right use cases for AI?

By looking at the work, not at the technology. The best candidates are tasks that are frequent, slow, error-prone and done on data you already hold: matching records, reading documents, answering repeated questions, forecasting.

What do we get at the end of a consulting engagement?

A written, prioritised list of what to do, what each would take, what could go wrong, and a scoped first stage. It is yours to act on with us or with anyone else.

Tell us how the work runs today.

How the work runs today, what the system must do and what it has to connect to. A person reads it and replies honestly about whether to buy, extend or build.

Fig. 06Quantum Beetle

Contact

Hire the
swarm.

Tell us what you want the swarm to do. We'll tell you honestly whether it can — and what it would take.

hello@quantumbeetle.ai