Less re-keying, faster answers, field teams you can follow. We start from a problem your teams hit every week and build the smallest tool that solves it, connected to what you already use.
In an industrial company, time is not only lost on the shop floor. It is lost in the office and on the road too: hunting for a part number across three catalogues, re-typing a service report, chasing a forgotten quote, reading a tender specification the night before the deadline. In the EY and Novation City Industry 4.0 barometer (2022, 74 Tunisian companies), marketing and sales came right after production among the functions to digitise, and only 10% of the companies had a formal 4.0 strategy. Many want to move; few know where to start. Our answer: one measurable problem, solved on a small scope first.
An assistant searches your catalogues, price lists and stock, suggests the part and its equivalents, and drafts a quote for the salesperson to approve.
An assistant that answers from your own catalogues, manuals and datasheets, in French, Arabic or English, and cites the page behind each answer.
Photos, parts used, customer signature and voice notes on the phone; the report reaches the office ready for invoicing.
The useful fields extracted, inconsistencies flagged and the data sent to your ERP. A person checks the doubtful cases instead of typing everything.
Simple quote tracking, follow-ups prepared automatically, and a dashboard by region, fed by the data you already have.
An assistant reads the specification, extracts the requirements and produces a compliance grid. The decision and the signature stay yours.
From an export of your item file: duplicates, dead stock and reorder alerts on critical parts. We work with your ERP, we do not replace it.
You describe one specific problem and your context. We try to understand the project and see together whether we are the right partner. We tell you plainly whether AI or software can solve it, or not.
One process, one team, with one simple measure agreed at the start: time to quote, time from service visit to invoice, number of documents re-keyed.
Your teams use the tool, we measure, and we extend it if it earns its place.
We work in French, Arabic and English. Your data stays under your control, and we tell you from the start where it is hosted and which AI models are used.
Predicting a failure takes sensors, a history of measurements and often an automation integrator. We organise preventive maintenance (schedules, reminders, history per machine) and analyse the data you already have.
We connect to it, through its API or its exports.
The figures in our articles come from public studies, with their source. The real gain depends on your situation; we measure it with you on a small first scope.
No. Many projects start with spreadsheets, PDFs and WhatsApp. If you have an ERP, we connect to it.
In most cases, yes. Scanned catalogues need a text-recognition step, which we test on your documents before committing.
Yes, which is why our assistants cite their source and a person always approves what goes to the customer. The tool prepares; your team decides.
It depends on the solution chosen, and we tell you before we start. Where needed, models hosted locally or with a host of your choice are possible.
For a small scope (one document type, one catalogue, one field form), think weeks rather than months. We set the timeline together after the first conversation.
We do the software side of maintenance: schedules, reminders, history, analysis of existing data. We do not install sensors and we do not promise to predict failures.
Pick one problem and describe it in a few lines: what happens today, who is involved, what it costs you in time. We get back to you quickly, usually within 48 working hours, for a short conversation: to understand your project and see whether we are the right partner to build it with you.