Same machines. 15% higher yield.
Our #SmallData approach makes expert-level manufacturing performance reachable for any operator, on any process.
WORKS FOR
Laser cutting
Injection molding
Robotic welding
Machining
SinteringWhy we exist
Everything we use is manufactured. GaussML exists to make manufacturing more sustainable.
Humanity will not manufacture less, so we must manufacture better. A process running at its best requires less material, less energy, and less machine time for every part it produces. That is what sustainability looks like on a factory floor: not an ESG report, but operational excellence.
Getting there has always been one of the hardest problems in production, and we made it our craft. Manufacturers come to us to win on cost and quality. Every one that does leaves industry a little leaner. At GaussML, your business is our mission.
The shift
Expertise shouldn't be the bottleneck.
Every machine needs carefully balanced parameters for each part it makes, and getting them right has always demanded scarce, hard-won expertise. With competition tightening, energy prices swinging, and supply chains under strain, every percent of machine productivity counts, yet the experts who know how to find it are retiring faster than they can be replaced. The knowledge that decides quality and yield is exactly the knowledge getting harder to find.
Our #SmallData approach changes what that takes. Expert-level parameters can now be built directly on the machine, in production, by the people already running it, learning from each part rather than from years on the job. With our solutions, every operator becomes an expert, in weeks instead of years. We start where that gap costs the most, in the parameters that decide quality and yield.
Why #SmallData works
Lots of data. Little knowledge.
01
Volume isn't knowledge.
A factory records oceans of data, but most of it looks the same. The handful of settings that decide quality and yield are barely represented.
02
Every experiment costs.
On a real machine, each trial burns material, time, and capacity. Brute-forcing the answer across thousands of runs was never an option.
03
So we learn from a few.
Our #SmallData approach reaches expert-level settings from a handful of guided runs on the machine itself. Little to integrate, and your process data never leaves the floor.
What expertise unlocks
Expert-level performance, on every machine you run.
More from machines you already own
Higher yield and throughput from the same floor, so you find capacity you didn't have yesterday without buying a single machine.
Expertise that stays
The know-how that used to retire with your best people is built on the machine and kept there. New operators reach it in weeks, not years.
Every run easier than the last
Each optimization sharpens the next, so the best settings come faster every time, bending the work toward optimization that runs itself.
The team
Born in research. Proven on factory floors.
The expertise to run machines well is scarce, and it is retiring. Dr. Jonathan Spitz saw that coming and knew his #SmallData approach could close the gap. The method was born in research, teaching machines to reconcile their digital twin with reality from very little data, first on humanoid robots during his postdoc at Inria, France's national institute for AI, then on industrial systems as a research scientist at the Bosch Center for Artificial Intelligence.
That approach now has a company around it. Engineering is led by Dr. Benjamin Rabe, who specializes in AI for production processes. Sales is led by Stefano Chiavegati, who spent over two decades leading marketing and sales at global technology companies including GE, Intel, AMD, and HP. Behind them, a growing team of engineers turns it into something operators use every day. With over five years of putting it to work in real factories, we speak your language and have proven ourselves the only way that counts on a shop floor: with results.
Over 40 years of combined experience, built at
Proof in the world
A competitive advantage, with the machines you already run.
We have proven this in production, from job shops to OEMs. On average our customers gain 15% more productivity, and the exact gain varies by process, across machining, injection molding, sheet-metal cutting and welding.
A gain like that compounds across an operation. It frees capacity from machines already on the floor, opens room to take on more orders, and pushes the next round of capital spending further out. More of the business, carried by the machines you already own.
We increased productivity by more than 30%, with consistently high quality. The decisive value lies in the speed and efficiency of the optimization: results that usually demand a great deal of a process expert's experience and time can be reached significantly faster and with less manpower.
Trusted by manufacturers, large and small
Where this is heading
Fewer experiments, fewer clicks.
Every parameter found on a machine sharpens the next search, so each run takes fewer experiments and fewer clicks than the last. We are making optimization as easy as any prep step on the machine, within reach of any operator who wants it.
Part of Europe's deep-tech ecosystem
