But concretely?

AI is a new technology and it is not always clear what it can be used for in your own line of work. Here are concrete examples, to see what it can change day to day.

01

Supplier prices change so often that it is hard to put your quotes together

The problem

In a construction company, the team looks up prices from recent quotes, then checks with suppliers. Rates change. They may reuse an old price without realising it is no longer valid.

The solution

We set up a conversational assistant that finds past quotes and checks supplier rates when up-to-date access is available. It shows prices with their source and date.

The team describes the need.
The assistant searches quotes and the rates it can access.
It presents the prices, their sources and dates.
The team approves the final price.
02

You spend a lot of time going through paperwork

The problem

A tender runs to several hundred pages. The team cannot always read everything before deciding. Yet a clause on deadlines, penalties or liabilities can make the response unsuitable.

The solution

We define your criteria and organise the documents. AI does a first screening and flags the passages to review, with their document and page of origin.

The team sends the file and its annexes.
AI looks for the defined criteria.
It presents a summary and the sourced passages.
Management decides whether to respond.
03

You have already done the work but it is hard to find again

The problem

The knowledge sits in old quotes. The team looks for the right references, copies lines and adapts the document. They start over with every request.

The solution

We organise a knowledge base. An assistant finds similar quotes using document retrieval, known as RAG, then prepares a draft with the assumptions and missing information.

A new request arrives.
The system finds similar authorised quotes.
The assistant prepares a draft.
The team adjusts and approves.
04

Your teams spend hours sorting and answering the same e-mails

The problem

Customer requests arrive by e-mail and look very alike: order status, delivery time, a document to resend. Each one means looking for the information in several tools before replying.

The solution

We set up an assistant that sorts messages, finds the answer in your documents and tools, then prepares a draft with its sources. A person reviews and sends each reply.

An e-mail arrives.
The assistant identifies the topic and looks for the information in your documents.
It prepares a draft reply with its sources.
A person reviews and sends it.
05

Entering supplier invoices takes you ages

The problem

Invoices arrive as PDFs, by e-mail, in different formats. Someone opens them, retypes the information into the management software and checks it matches the order.

The solution

We set up a tool that reads the invoice, extracts the information and matches it with the order. It flags price, quantity or reference gaps, and prepares the entry in your software.

The invoice arrives by e-mail.
The system extracts the information.
It matches it with the order and flags gaps.
Accounting approves or corrects before posting.
06

Your orders arrive in every form and you retype them by hand

The problem

Customers order by e-mail, PDF or message. Each order has to be retyped, references and prices checked, then created in the ERP. Typing errors are often found too late.

The solution

We set up an assistant that reads the request, finds the references and the customer’s terms, then prepares the order as a draft in your management software. Doubtful references are flagged.

An order arrives by e-mail or PDF.
The assistant identifies the customer, items and quantities.
It creates a draft order and flags doubts.
The sales rep approves the order.
07

You forget to follow up on quotes and overdue invoices

The problem

Follow-ups come after everything else. Quotes stay unanswered, invoices pass their due date, and nobody has time to go through the files one by one.

The solution

We set up a system that spots pending quotes and invoices, checks each customer’s history and prepares a suitable reminder. You choose what goes out.

The system spots pending quotes and invoices.
It checks the customer’s history.
It prepares a suitable reminder.
A person approves sending.
08

Your meetings end without minutes and actions get lost

The problem

After a site or management meeting, nobody has time to write the minutes. Decisions and actions to follow up end up in scattered notes, or nowhere.

The solution

With the participants’ consent, we set up a tool that transcribes the meeting, writes structured minutes and lists the decisions, actions and owners.

The meeting is recorded with the participants’ consent.
The system writes the minutes.
It lists the decisions and actions, with their owners.
The participants correct and approve.
09

Your employees keep asking the same questions about procedures

The problem

The procedures exist, but they are scattered and sometimes outdated. Newcomers, and even long-standing staff, end up asking a colleague instead of searching.

The solution

We organise your procedures in a knowledge base and set up an assistant that answers by citing the source document. It also flags contradictory or outdated procedures.

An employee asks a question.
The assistant searches the up-to-date procedures.
It answers by citing the document.
A reference person corrects the flagged documents.
10

You think you need AI when a calculation would do

The problem

Some problems look like an AI topic when they are really a calculation: planning routes, grouping orders, optimising packing. AI would sometimes be more expensive, less predictable and harder to control.

The solution

We start by checking whether a classic rule or algorithm is enough. If so, we build it without AI, after comparing it with an AI solution. Knowing when to give up on AI is part of consulting.

You describe the problem and its constraints.
We test a classic rule or calculation.
We compare it with an AI solution.
We keep the most reliable and least costly solution.
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