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AI Lab

AI that your teams build and own

We do not sell a black box. We coach each function to build working applications on its own data, inside its own environment.

The coaching programme

01

Build

Weekly coaching per functional team. Each team picks a real problem and ships a first working application.

02

Iterate and share

Teams improve their tools with real use, and show them to each other. Common patterns are packaged.

03

Handover and scale

Code, documentation and playbook handed over. A showcase to leadership and a plan for what comes next.

Track 1: team coaching

One hour per team per week, on the team’s own use cases.

Track 2: C-level coaching and advisory

Face to face with each leader: learn about AI through tangible, hands-on approaches, define what it means for the company, steer the change, and work through the strategic and operational topics in their scope.

Worked example

A weekly business review, read by an AI finance expert

A DIY retailer with 10 stores in one country. The dashboard is interactive, the management comment is written live, and the AI reconciles both into a one-page executive summary.

Demo on synthetic data. The analysis runs in your browser. In an engagement it runs on your own data with a language model, inside your environment.

DIY retail · 10 stores · France
All stores
Net sales, last 13 weeks
Stores, this week

Click a store bar to focus on it.

What moved net sales vs last week

Management comment

Written by the retail director every Monday. Click the button to write it.

Simulate the weekly comment first.

Empty. Launch the AI analysis once the comment is written.

Empty. Generate the corrected summary once the analysis is done.

Landed-cost estimator

Enter a shipment to see an indicative range for what it really costs once it reaches your warehouse.

Indicative landed cost –

Uplift on goods value: –

VAT excluded. Ranges only; real rates depend on carrier, season, product classification and contract.

Indicative figures, validated in an engagement. Not a quote.

AI-readiness diagnostic

Eight quick questions and one open question. You get a readiness profile and the three use cases we would start with.

Which teams would you like to bring into AI first?

Pick one or more.

1 Key operational data is available in one place and trusted by the teams.
2 Data is clean enough to be used without weeks of manual preparation.
3 Our main processes are written down and followed consistently.
4 We can name an owner and a measurable KPI for each process.
5 Team members already use AI tools in their daily work.
6 Managers can describe a problem clearly enough for a team to build a solution.
7 Leadership has set rules on what data may be used with AI.
8 There is a named sponsor and a budget or time allocated to AI.
9 What is the first problem you want to solve?

Optional. In your own words; a sentence or two is enough.

Calculated in your browser. Nothing is sent or stored.

Pick an origin and a European gateway, then compare sea, rail and air.

Route explorer: Asia to Europe

Star projects

Real problems, solved by the teams themselves

Applications built by the teams of a regional retail group during an AI coaching programme. Each one starts from a problem a team lives with every day.

12 projects

  • Finance

    Store P&L tracker

    Problem

    No central tool to track and analyse store P&L across several Asian markets.

    Solution

    One tracker that consolidates store P&L by market and cost line, with drill-down to each store.

  • Finance

    CapEx navigator

    Problem

    Capital expenditure and store investments are complex to manage across a region: funds are misallocated and the return is hard to follow.

    Solution

    One place to plan, approve and follow capex and store investments, with the return tracked project by project.

  • E-commerce

    Dispatch sales dashboard

    Problem

    No real-time view of e-commerce dispatch and sales, so decisions come too slowly.

    Solution

    A live dashboard of dispatched orders and sales that teams can act on the same day.

  • Merchandise

    Engagement-letter tracker

    Problem

    The process for managing letters of engagement is unclear and inefficient: delays, compliance risk and lost revenue.

    Solution

    A tracker that follows each letter through its stages, with an owner, a status and alerts.

  • B2B

    B2B platform

    Problem

    No efficient central platform for B2B transactions: scattered communication, manual work and missed opportunities.

    Solution

    A single B2B portal for orders, quotes and customer exchanges.

  • B2B

    Bulk sales platform

    Problem

    Corporate sales are managed by hand: missed opportunities and a heavy administrative load.

    Solution

    A corporate-sales support app that runs bulk deals from request to order.

  • Marketing

    Social media insights hub

    Problem

    Hard to track the performance of the official social account and its audience engagement, which limits marketing optimisation.

    Solution

    A marketing BI dashboard that monitors the activity of the official Instagram account.

  • Marketing

    Member engagement platform

    Problem

    Customers are not actively engaged, which weakens loyalty and raises the risk of churn.

    Solution

    A member platform to engage customers and bring them back.

  • Store operations

    Store performance dashboard

    Problem

    Hard to track and analyse store sales by SKU, vendor and brand, so decisions come late or are not optimised.

    Solution

    A store sales dashboard by SKU, vendor and brand, with week-to-date and month-to-date views.

  • Merchandise

    Vendor hub

    Problem

    Vendor management is manual: inefficiency and higher operating costs.

    Solution

    One hub to manage vendors and their information in a single place.

  • Supply chain

    Import planning dashboard

    Problem

    Import planning (monthly, weekly and seasonal) relies on manual, disconnected processes: forecast errors, late shipments and higher inventory costs.

    Solution

    A dashboard on the company data lake that brings import and direct-import data together for monthly, weekly and seasonal planning.

  • Project management

    Project follow-up app

    Problem

    No central way to follow project progress for a local subsidiary, which causes delays and communication breakdowns.

    Solution

    A project follow-up app with Gantt and Kanban views.

The client and the team members stay confidential.

Build yours with us