The Case of Minoterie Forest

What is your role within the company?

As a Credit Manager, my role is to understand our economic environment in order to make the right decisions: analyzing risks, monitoring our clients’ financial health, and guiding collection efforts with a focus on return on investment.

Background to Minoterie Forest’s contact with Infolegale

What challenges were you facing?

Our business operates in a high-risk sector. On average, 5 to 6 companies in our portfolio enter bankruptcy proceedings each month, and credit rating downgrades occur regularly. We must therefore maintain constant vigilance over several hundred clients.

But the real challenge stems from changes in the baking industry. Today, we’re no longer talking solely about traditional artisans. We’re seeing entrepreneurs emerge who buy out companies in liquidation, restructure them, replace management, and sometimes leave unpaid suppliers in their wake.

In this context, my goal was not only to gather information, but above all to understand the economic reality behind these businesses so I could make better decisions.

Had you already tried other solutions or methods? If so, why weren’t they satisfactory?

The main problem with traditional methods is the time spent collecting and consolidating data.

A Credit Manager would spend an enormous amount of time retrieving information from their ERP system, exporting data, consulting various tools, compiling everything in Excel, and then building their analysis.

Ultimately, a large portion of their energy was spent producing the analysis, when our added value should lie elsewhere.

As I often say, what’s expected of a credit manager is to understand the situation in order to make decisions.

Certain approaches certainly provided data, but not necessarily the understanding needed to make a relevant decision quickly.

Fred., a true co-pilot for the Credit Manager

What convinced you to subscribe to Fred. AI?

I first tested Fred. without really having the time to focus on it. I’d already been using artificial intelligence for several years, so I didn’t immediately grasp the tool’s full potential.

Then, after a month, I really got into it and found the tool simply extraordinary.

So much so that today, I tend to use nothing else. In fact, I’ve updated our contract to integrate Fred. into our daily use of Infolegale.

What convinced me was its ability to go far beyond a simple information search: Fred. understands the business context and provides an analysis that’s immediately actionable for decision-making.

How do you use Fred in your analyses?

One of the most powerful uses is analyzing our own sales data.

For example, I feed Fred. several months’ worth of flour invoices. It’s able to identify a baker’s business profile: whether they mainly sell bread, are expanding into snacks, or focus more on pastries, etc.

What surprised me most was Fred.’s ability to understand my business.

Fred.: A More Insightful Advisor Than Traditional Methods

One of the most striking aspects concerns dispute resolution advice.

We’ve been working with several debt collection agencies for a long time. However, when I present a complex case to Fred., I find his recommendations more relevant because they take my business logic into account.

My goal isn’t to initiate legal proceedings systematically; it’s to achieve the best possible return on investment. If a proceeding costs more than it will yield, it’s not worth it.

Fred. fully understands my return-on-investment concerns and goes much further in his advice.

It’s this ability to think like a credit manager that makes all the difference.

Do you have any specific examples?

The most telling example involves address analysis.

For a long time, we mainly checked the executives when opening a customer account. In reality, in our industry, it’s not always the manager who provides the key insights: it’s often the business assets and addresses that tell the story.

Thanks to Fred., I was able to instantly reconstruct the history of a single address over fifteen years, identify several successive companies, and uncover patterns of repeated liquidations that had cost us tens of thousands of euros.

Before Fred., I don’t think we were able to map this out. Today, we get that information instantly.

What are the main benefits you’ve seen since implementation?

The main benefit isn’t just the time saved— it’s the shift in where value is created.

Before, we spent our time gathering data. Today, we can finally focus on what really matters: understanding our environment and customer profiles, detecting risks that were previously invisible, and making better decisions.

The most interesting thing is that the tool doesn’t replace human expertise.

It allows me to focus my expertise where it’s most valuable.

How did the implementation go?

Getting started was very straightforward. We were already using Infolegale’s solutions for portfolio monitoring; I simply updated our contract to include Fred.

The only real learning curve was figuring out how to craft high-quality prompts to fully leverage the tool’s capabilities.

As with any artificial intelligence, the more structured the query, the more relevant the response.

Once we got past that stage, adoption happened very quickly.

Looking back, what are your main sources of satisfaction?

Overall, we’re very satisfied with our collaboration with Infolegale.

In my opinion, Fred. represents a real opportunity for the credit manager role. In my view, a professional who doesn’t use a tool like this is missing out on a significant lever for improving efficiency and accuracy.