Medical technology

AI in medical technology.

Product data, documentation, dealer materials and connected devices: we apply AI where manufacturers face the most manual work today, with traceable approvals.

Milled instrument tray of white Calacatta marble holding forceps, micro scissors, a probe, a needle holder and an instrument handle in titanium and champagne metal; moss, gray-green lichen and an olive branch with green olives grow in each of two hollows, and a sensor with a braided cable lies in the milled channel

Dealer materials

4 languages
Brand check

Sample view

Device service

Update verified
Log saved

Sample view

Exploded view of a surgical handpiece on white Calacatta marble: cannula, silicone sleeve, cone, O-rings, spring and knurled handle housing in champagne metal, laid out in a row; a braided cable lies in a milled groove and is plugged into a socket, and moss, lichen and an olive branch with two green olives grow in a hollow
A focused pilot becomes a production system, with integration, testing and human oversight from the start.
Baybora GülecFounder

The gap

A lot of knowledge, little time, strict rules.

Medical technology manufacturers work with large volumes of product data, documentation and translations. Much of it is still transferred by hand. AI can take some of that load off, but only with clear rules, traceable approvals and data that stays in-house.

Our view

The fastest value isn't in the lab but in the documentation.

Before AI turns to development or diagnostics, it can take manual work off your hands: in product data, dealer materials, translations and device service. There, the value is quick to measure and the risk is manageable.

Open documentation binder in sand-colored linen with a champagne-metal ring mechanism on a long Calacatta slab; along the spine, a strip of moss with lichen and an olive branch with green olives grow along a braided cable, and a flask and test tubes stand behind it

Approach

How we work in regulated environments.

Book an intro call
  1. Step 1

    Clarify

    Use cases, data situation, regulatory classification

  2. Step 2

    Test

    Pilot on real, approved data

  3. Step 3

    Build

    in your systems, with an approval workflow and log

  4. Step 4

    Hand over

    Documentation for your quality department, training, operations

Let's talk about your documents and devices.

20 minutes. We'll point out where AI will help you first.

Stepped pyramid of three twisted frosted-glass cubes with moss, olive branches, granite and cables