Self-optimizing E-Commerce

Award-winning Artificial Intelligence solutions based on adaptive Deep Reinforcement Learning.

Our specialty: Mobile Commerce.

Our partners

NVIDIA EXIST IBP Cyberport

Product

Today, optimizing conversions is done using simplistic methods like A/B testing.
We handle the complete package of personalization for mobile commerce right out of the box.

Conventional approaches

Conventional approaches are iterative by design. Therefore, experiments can only adapt to environmental situations that lie in the past, and become outdated very fast.

Features of stores are usually optimized in isolation, without regards to the bigger impact on the customer lifecycle. While this simplifies the algorithmic challenge, it also severly limits the total achievable uplift.

Conventional methods have a significant need for manual intervention. They usually demand a constant creation of hypotheses, checking of segments for consistency and interfacing with IT for implementation.

Explored uplifts suffer from a significant delay between findings and their exploitation. In dynamic environments, that can even lead to vanishing uplifts.

Conventional Machine Learning is heavily dependent on the quality of a process called feature engineering. This approach is very expensive, error prone and not robust to changes in the environment.

Many classical Machines Learning algorithms are not easily scalable. That leads to severe problems as the data set grows.

Free Machines

By fundamental design, our algorithmic core is able to continuously adapt to new situations. Designed as an end-to-end decision system, it is built to be deeply integrated into production systems and therefore can instantly react to changes in the data.

Instead of focusing on single features, our algorithm enables a sustainable optimization of the whole customer lifecycle. This can include the long-term goals that actually matter to your business.

After the simulation period, where the system learns behavioural structures of your business and your customers, the systems constantly moves towards a very high degree of automation. With extensive monitoring capabilities, we allow you to focus on the big picture.

The system continuously learns and is able to exploit these findings in real-time. You'll never again will have to wait for the next optimization iteration.

free machines is built upon state-of-the-art Deep Learning approaches. Manual feature engineering is replaced by deep network architectures that learn the optimal feature set automatically.

Our algorithmic core is built on highly scalable tensor arithmetic, it is extremely scalable on GPUs. Data access is handled by a redundant, high-availablility web interface. Therefore, we are capable to handle very large datasets.

Benefits

That sounds great, we hear you say, but how does it drive conversions?

Speed & smooth UX

Nobody likes waiting for a shop to load, and the strong effects on bpunce rates of slow shops are well understood. Enjoy lightnig speed with the Free Machines frontend.

Offline capability

Using Progressive Web App technology, our shop frontend works even when the network is poor. This is crucial on mobile, where the network is often unreliable.

Artificial Intelligence

On mobile, content is king. We employ advanced AI to ensure that your users find the content that is relevant to them in the shortest amount of time.

What our customers say

Mueller
Birgit Müller

Marketing Director
riskmethods

Thanks to the contextual personalization of Free Machines, we were able to generate a conversation rate of 11.9% already in the first 4 weeks.

Zirngibl
Michael Zirngibl

Founder / CEO
interact.io

Very impressive technology! Using it, we were able to raise the conversion rate for new customers by almost 69%.

Schild
Florian Schild

Founder / CEO
boot.ai

We think Free Machines is the way to get rid of cumbersome A/B Testing.

A radically simple pricing, ensuring positive ROI

We succeed if you succeed.

1. Setup

Free
  • Activate add-on
  • Setup SSL certificate

2. PoC

15% of uplift
  • 50% control group
  • Real-time uplift measurement

3. Live

30% of uplift
  • Ongoing
  • Reporting & Monitoring available

Team

Profound market knowledge.

HL
Dr. Hannes Lüling

CRO

Hannes holds a PhD in computational neuroscience from the Technical University of Munich. After several years as Senior Data Scientist at ProSiebenSat.1 Digital and BMW, he is now heading AI research at Free Machines.

OS
Dr. Olav Stetter

CEO

Olav is a physicist by training, with a PhD on the dynamics of complex systems. He also has extensive experience building technologies, teams and products in lean startup environments.

US
Dr. Uwe Stoll

CTO

Uwe has worked as a Senior Machine Learning Expert for several startups and enterprise clients. He can build on a PhD in Semantic Web and Machine Learning, during which he did extensive research in the field of e-commerce.

Career

Work with us on the future of Artificial Intelligence.

Working Student: Real-time Web Development

Location: Munich, Germany

Job ad (PDF)

Freelancer/Working Student: Growth Marketing

Location: Munich, Germany

Job ad (PDF)

Where we are

We currently reside in the "Retailtech Hub" in Munich.

Contact Us

Feel free to drop us a line, and we will get back to you as soon as possible.

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Funding