Revealing future manufacturing technologies

Accelerating unseen innovation through AI-supported research, development, and manufacturing — unlocking superior efficiency and intelligence in every step of industrial production.

Our Team

The minds driving Betteryields

A few months, dozens of whiteboard sketches, and at least one questionable vending machine dinner later, we built our first guided experiment module.The next yield report? Up 17%.Someone muttered:
“Well that’s... better yields.”
And that was it.
The name stuck.
The process improved.
The yields kept getting better.

Today, Betteryields is where structured experimentation meets engineering intuition – helping teams turn chaos into clarity, and tests into results. Because better processes really do lead to better yields.

And that’s why we’re called Betteryields.
Dr. Aaron Hutzler
Production Technology & Processes, CEO, Founder
Dr. Aaron Hutzler
Software Engineering & Data Science, CTO, Founder
Head of Sales
Seth Homer
Head of Sales & Marketing
Florian Pechler
Software Engineering & Data Science

Our Mission

We are building an AI supported engineering notebook (AISEN) to uncover hidden innovations and accelerate the next generation of manufacturing.

Why we are building the Yieldmanager

We are a cross-functional team of manufacturing engineers, software developers, process experts, and sales engineers.


We’re building the Yieldmanager to solve a core problem we’ve encountered across every layer of industry:
"In theory, engineering is repeatable and reproducible.
 In practice, it often isn’t."

Despite all the systems in place, critical process knowledge is often undocumented, inconsistently applied, or simply lost. As a result, successful processes cannot be reliably repeated—especially under pressure.

We've Seen the Cost

  • Deep-tech startups collapsing—not because the core technology failed, but because stable production couldn’t be achieved in time.
  • Process teams spending months rebuilding results they already had—because no one could find the exact setup again.
  • Production launches cancelled because validation wasn’t traceable.
  • A process that worked in one facility but failed in another—without anyone able to pinpoint why.
  • Critical audits failed due to inconsistent documentation and incomplete data.

The Status Quo Is Broken

  • Experiments are tracked in Excel or ad hoc tools—often with missing context.
  • Cp/Cpk calculations are skipped or retrofitted.
  • Trial settings are recorded once, then overwritten or forgotten.
  • Engineers waste time redoing instead of scaling.

This isn’t just inefficient—it’s a systemic barrier to process reliability and scale.

Our Perspective

  • Manufacturing engineers on our team have run the same experiments five times just to get clean data.
  • Software engineers build tools that fit directly into real engineering workflows—with minimal overhead.
  • Process experts define what matters: structure, traceability, robustness.
  • Sales and support stay in feedback loops with real users to validate every design decision.

What We’re Building

  • Structured experiment workflows with version control and traceable settings.
  • Built-in statistical evaluation — Cp, regression, correlation — so analysis happens where the data lives.
  • Automatic documentation of parameters, timestamps, batch numbers, operator inputs.
  • Transferable process knowledge, ready for scaling across products, shifts, and facilities.

Our goal is clear:  Make reproducible engineering the default—not the exception. And we’re building Yieldmanager to get us there.

Join a talented team

Stay ahead of the curve and get a demo of the Yieldmanager capabilities!
Get in touch with us