We bring machine learning to the supply chain and unlock untapped savings





Benefits



Increase Profit

Save 5 to 10% on your total purchasing costs and get a direct impact on the gross margin


Master complexity

Handle the specifics of your company with ease. Even factors such as quantity discounts, storage constraints or perishable items


Automate easily

Get the optimal order plan anytime and within seconds while maintaining existing IT infrastructure and business processes



What is GenLots?


GenLots is a platform which applies machine learning concepts
to a very specific industrial problem:
​The computation of the optimal order plan.

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Frequently asked questions


A young pretty businesswoman looking up and standing in front of a blackboard with many different graphs drawn on it. Front view. Concept of presenting data in graphs.

We have optimized a lot already. How can you save us money?

Assessing inefficiencies in purchasing is very difficult without a benchmark, namely the optimal order plan. As a result, many hidden costs remain tied in the purchasing process. Traditional models fail to detect such hidden costs – by presenting results which are acceptable but simplified.

GenLots technology now allows to obtain this benchmark and remove unnecessary costs of about 5-10% depending on the raw material ordered

Why has this not been done before?

We see three aspects to the answer.

1. There is no general awareness of the hidden costs tied up in the purchasing process.

2. There is no Total Cost of Ownership approach when it comes to procurement, as each department is focused on his silos.

3. All trade-offs (such as perishability, fixed lot sizes, etc.) are not taken into account due to complexity.

GenLots’ journey initially involved academic research, which allowed our team to uncover those hidden costs (1). We were astonished by the amounts involved.

We started developing models to tackle this problem, embracing a company-level view (2) and using machine learning concepts, a technology that proved adaptable and fit to our challenge: handling complex constraints with ease and velocity (3).

Our tested solution now represents a paradigm shift in order planning.

Can GenLots be applied to my company?

To assess what proportion of your orders is eligible for an optimization through GenLots, we conduct a quick historical analysis of your most recent purchasing plans.

The result are provided within a week at no cost and allow to gauge the potential of savings precisely

In process-oriented companies between 20% and 70% of purchases are usually eligible for optimization. On those orders we can generate substantial savings.

Is GenLots only focusing on order planning?

Presently yes. Vast and sustainable savings can already be derived with the GenLots order planning product. That said we are developing extensions of the product focusing notably on demand forecasting and production lot sizes, building on best-of-class technologies to get rid of more unnecessary costs tied up in the system. We are currently looking for industrial partners for those research projects. If interested just contact us in the form below



News and Press


Nice seeing @DeepMindAI exploring the potential of Reinforcement Learning. At GenLots we use the same methodology (… https://t.co/fhbPysAg2r
h J R
@genlots
A good summary for all who want to know what makes good data scientist #ML https://t.co/EPuDwskNwz https://t.co/hYXmX9CVu3
h J R
@genlots
Our founders are coming to Milano Today through Wednesday. Let us know if you want to meet up.
h J R
@genlots



About GenLots


Simon Schenker

Simon Schenker

Co-Founder, Strategy, Product & Delivery
Arnaud

Arnaud

Co-Founder, Strategy & Investor Relations
Victor Bassili

Victor Bassili

Industry Advisor, Formerly McKinsey, BASF, Ciba, Shell

+ Highly dedicated development team in Switzerland
+ 4 private investors

Originated at the Swiss Federal Institute of Technology Zurich (ETH Zurich), GenLots SA is driven by a highly motivated team of engineers and business professionals located in Switzerland


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