Four capabilities already put to the test.

The problem

Manuals, technical files, instructions: to show that they comply with a directive, a regulation and the harmonised standards, hundreds or thousands of requirements have to be checked one by one, searching the document by hand. For machinery manufacturers, Regulation (EU) 2023/1230 applies from 20 January 2027.

What we build

A check built on the standards that apply to you. For each requirement the model searches the whole document, reads it more than once, decides and writes the outcome with the citation: the page and the passage it comes from. The model is open-weight, chosen for the task and specialised by the procedure of the check, and runs on your machines or ours.

What you get

The report requirement by requirement, with the outcome and the citation, which your expert checks and signs. When the document or the standard changes, the check is run again.

The problem

PDF manuals, scanned pages, technical drawings, tables running over several pages: they hold the codes, values and spare parts needed every day, but nobody can search them. Automatic reading tools, used on their own, lose exactly the codes.

What we build

A chain of open-weight models chosen for your documents: small models for text and tables, a large model for figures, drawings and scans. We put them together and tune them for the task; at the end a check makes sure no word of the PDF is lost and compares every number with the page. Everything happens on your machines or ours.

What you get

For each document a structured file, with the position and source of every piece, and text ready to search or to pass to your software.

The problem

Anyone who makes or sells a material recognised by sight, such as a stone, a wood or a fabric, needs new, credible images: at true scale, at the resolution of their best photographs, neither copies nor enlargements.

What we build

One model for each type of material, trained by us on your images: an open model fine-tuned on your files, or networks of our own trained from scratch. The detail is generated, not enlarged. First we stitch the photographs of real surfaces into a single image at true scale: it is the yardstick against which we measure the generated ones. Training and generation run on our machines or yours.

What you get

The generated images, at true scale, to look at enlarged down to the detail, and a separate model for each type of material.

The problem

Deadlines with several authorities, case files to follow, documents to keep in order, communications to prepare and mailboxes always full. The information is there, but scattered: whoever holds it together spends the day looking for it.

What we build

A shared model of the organisation, that is a single ontology, for deadlines, contacts, rules, documents and communications, and an AI agent working inside it: it reads the mail, follows the case files, prepares replies and texts. The agent works with the model best suited to the task, open-weight when the data cannot leave: in that case on your machines or ours. It changes nothing on its own: it proposes, and a person decides.

What you get

The work already prepared, one place to find deadlines, documents and communications, and the log of every step of the agent: what it read, what it proposed, who decided.