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Lab Productivity AI 

Our lab-integrated AI software assists chemistry and materials teams in optimizing formulations, processes and experiments. Our AI constantly generates knowledge with each experiment, so you avoid dead ends and bring innovations to market faster.

AI Enterprise Software | AI Strategy Consulting 

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R&D will always be challenging. But much of the friction is avoidable.

Chemistry and materials R&D is inherently complex. But too often, the hardest part isn’t the science itself. It’s the way work is organized around it. 

Trial-and-error does not scale

Your team runs hundreds of experiments a year. In complex, multi-variable problems — formulations, catalysis, process optimization — even experienced researchers can spend months exploring without converging. Not because they lack skill, but because the search space is simply too large for intuition alone.

Knowledge gets lost between teams

Bench optimizes a formulation. Pilot re-optimizes it under different conditions. Plant starts over again. Each group runs experiments that could have been informed by the previous stage — but context, assumptions, and results don’t travel.

AI is often a solution looking for a problem

Many AI tools push technology because it sounds modern, not because it helps scientists. The result: scepticism from experienced researchers, low adoption, and minimal impact. AI only creates value when it improves experimental decisions. Otherwise, it’s noise.

 busy scientist

A better way to run R&D.

Aixelo combines a pragmatic R&D framework (OPEL) with intelligent software (Edison 4.0) to help your team move from isolated experiments to coordinated learning.

 

Structure your R&D

Define objectives, map pipelines, and connect experiments to outcomes. Every experiment has a purpose.

 

Run smarter experiments

AI suggests what to try next based on what you’ve already learned. Fewer experiments, faster convergence.

 

Compound your knowledge

Learning accumulates across experiments, teams, and scales. No more starting from scratch at every handover.

From first experiment to compounding knowledge.

 

Step 1: Define your project

Define your workflow, parameter space, and what success looks like. 

 

Step 2: Run experiments

Edison suggests an intelligently selected first batch, which you run in your lab and upload the results.

 

Step 3: Learn and iterate

Edison learns from every result and suggests smarter next experiments to move you closer to your objective. 

 

 

Step 4: Scale and share

Knowledge travels with the data across teams and stages, from bench to pilot to plant.

Results that speak for themselves.

70–80%

fewer experiments to reach targets

2 weeks

to breakthrough (vs. months of trial-and-error)

€75,000+

saved in researcher time on a single project

From disconnected labs to a Knowledge Engine.

Most R&D organizations do not have a data problem. They have a knowledge problem. Experiments happen in isolation, results stay in notebooks, and knowledge is lost when people leave.
Aixelo turns this into a compounding knowledge system where every experiment builds understanding and creates a lasting competitive advantage.

Disconnected Labs

Isolated experiments. Knowledge resets at every handover. Teams repeat each other’s work.

→  Connected Pipelines

Shared objectives, shared data. Learning flows bench → pilot → plant. Context travels with the experiments.

→  Knowledge Engine

Every experiment compounds. AI-assisted decisions. Fewer wasted experiments, faster convergence, higher confidence.

The ultimate goal is not efficiency — it’s compounding knowledge. Your organization doesn’t just run experiments. It learns.

OPEL is how you structure AI-driven R&D. Edison is the software tool where you do it.

OPEL Framework

A pragmatic methodology for structuring R&D: define objectives, map pipelines, run coordinated experiments, and capture learning.

Learn more about OPEL

Edison 4.0

Web-based platform for adaptive experimentation. Define your workflow, set objectives, and let AI guide your experiments.

Explore Edison 4.0 

Ready to make every experiment count?

Pick a real project, not a demo. We’ll show you how Edison 4.0 fits your workflow in a 30-minute call.

Our Team

We are a Karlsruhe Institute of Technology (KIT) spin-out and pioneer closed-loop AI for accelerated innovation.

Christoph Kreisbeck Headshot

Dr. Christoph Kreisbeck

Co-Founder

Chief Executive Officer

Picture1_3

PD Dr. Manuel Tsotsalas

Co-Founder

Chief Technology Officer

Pascal Friederich Headshot

Prof. Dr. Pascal Friederich

Co-Founder

Chief Scientific Officer