AI audit & implementation · Small and mid-sized companies

AI in your business in a matter of weeks, without training your teams first.

I audit one area of your business, name the places where generative artificial intelligence would save you time, then build the systems with you. You take back the controls whenever you want.

Ten days on one area · A costed, workable plan at the end, client or not.
Measured impact 01

×15

traffic at a 20-person consultancy, from 10 to 150 visitors a day

Measured impact 02

×6

inbound enquiries, from one every three days to two a day

Measured impact 03

1 in 4

of those inbound enquiries turns into signed work

Figures measured on an acquisition build running since March 2026 for a 20-person consultancy.

Read the case study

The difference

The problem is not that your teams cannot use AI.

It is that nobody in the building has time to work out what ought to be automated, or to build it. A training course answers neither question. A system that runs answers both.

  • 01

    Measure before proposing

    The diagnostic starts from the time your teams actually spend, not from a catalogue of use cases. If an area holds no gain, I tell you so.

  • 02

    Build first, do not train first

    An AI course goes stale within months and still never says what to automate here. Build the system first, and your teams learn on the tool that exists.

  • 03

    Settle data privacy at the start

    Where the data is processed, whether it is kept, whether it trains a model: those are decided before the first line of code, not at acceptance testing.

How it works

Three steps, and you can stop after any of them.

Each step has a price, a timeframe and a deliverable. You decide on the next one from what the last one produced, not from a commitment signed at the outset.

  1. Recommended starting point
    01 10 days

    Diagnostic

    €9,500 excl. VAT · fixed fee, one area of the business

    Know exactly where generative AI would save you time, what it costs, and what to build first.

    • A map of where the time actually goes in the area audited
    • Each lever costed in hours freed, ranked by effort and by gain
    • The data note: what leaves your systems, and where it is processed
    • A three-month plan, naming the first system to build
  2. 02 4 to 6 weeks

    Pilot build

    from €18,000 excl. VAT · fixed fee, one system in production

    A first system genuinely running, used by your teams, with its gain measured.

    • The system built, deployed and connected to the tools you already use
    • A weekly demonstration, so you watch the build progress
    • The before and after measurement on the gain you were after
    • Hand-on training for the people who will actually use it
  3. 03 fixed fee or monthly

    Industrialisation and handover

    on request · depending on what you take over

    The system scales, it is monitored, and you take the controls at your own pace.

    • Installed on your premises, on your cloud, or hosted and run by Praedic
    • Monitoring and alerts, so you hear about a problem before your users do
    • Operating documentation and a handover to your own team
    • Extension to neighbouring areas, once the first gain is banked

The detail, week by week →

The levers

Five places where time goes missing, in almost every company.

Each is treated as a subject in its own right, with its typical builds, its timeframe and its own data privacy question. And each one is backed by a build that happened.

Data privacy

Your data does not leave without you knowing where it goes.

It is the first objection directors raise, and it is a fair one. It has precise technical answers, and which one applies depends on how sensitive your material is.

How I handle the question
01

One sensitivity scale, four different answers

From a programming interface under contract through to an open model running on a machine you control, depending on what you handle.

02

The questions asked before anything is built

Where the data is processed, whether it is kept, whether it trains a model, which subprocessors see it, and for how long it is retained.

03

What stays with you, spelled out

The architecture separates what may leave from what must not. Plenty of builds run on cut-down or anonymised data.

Anthony Crowther-Alwyn

10+ years in the field

Data science & AI in production

Who you are dealing with

Anthony Crowther-Alwyn.

Ten years of data science inside large French companies, then AI systems put into production at software publishers, retailers and customer contact centres.

Since March 2026 I have run generative AI adoption projects at my main client, a 20-person consultancy, and at a remote monitoring company. The results shown on this site come from that work.

"What I learned there fits in one sentence: the obstacle is almost never the technology, it is knowing what to build first."

The background in full

Guides

What I know, written down.

All the guides

Next step

Where would you start?

Ten days to map where your teams lose time, put a figure on each lever and name the first system to build. If AI is not the right answer, I will tell you so.

Diagnostic

Étape 1

10 days

€9,500 excl. VAT · fixed fee, one area of the business

  • A map of where the time actually goes in the area audited
  • Each lever costed in hours freed, ranked by effort and by gain
  • The data note: what leaves your systems, and where it is processed
  • A three-month plan, naming the first system to build