PSIwms AI AI-powered end-to-end analysis platform

Optimizing complex intralogistics processes

PSIwms AI platform is used to analyze data coming from a real-life warehouse, test best-fit solutions, and optimize processes with the help of artificial intelligence to make logistics more efficient.
Supporting warehouse management processes 1

Supporting warehouse management processes 2Supporting warehouse management processes

Are you wondering about the actual potential of your warehouse? Or looking for opportunities to optimize your operations? Do you want to find out "What if..."? Check the return on your investments and harness artificial intelligence to test new solutions.

PSIwms AI helps you pick the most optimum logistics strategy and evaluate the impact of potential changes on the efficiency of your processes. Use advanced AI algorithms and mechanisms that will drive the right business decisions.

Artificial intelligence in your warehouse 1Artificial intelligence in your warehouse

Using a digital twin, PSIwms AI will analyze various scenarios of warehouse operations and offer improvement recommendations, all based on artificial intelligence and machine learning solutions integrated directly with PSIwms. As a result, any changes in the physical warehouse are automatically fed into the digital twin and incorporated into your analyses in real time.

Artificial intelligence in your warehouse 2
Warehouse simulator

Digital TwinDigital Twin – a warehouse simulator

A Digital Twin reflects all key logistics operations and is linked via a suitable interface to the WMS. Simulations are based on real-life operational data and WMS functionalities.

Benefits of PSIwms AI

Benefits of PSIwms AI
Shortening goods picking paths

goods picking paths shorter by approximately

Higher process efficiency

process efficiency higher by more than

An option to analyze before implementation

an option to analyze process modifications before their implementation

Optimal creation of order groups

optimal creation of order groups

PSIwms AI sample screens

Key PSIwms AI components

Key PSIwms AI components

Capabilities of PSIwms AI

With PSIwms AI, you can perform high-precision simulations (based on real-life data) of any changes in the topology of your warehouse; predict the impact of newly purchased warehouse automation equipment on productivity figures; and verify whether the warehouse staff are able to handle the upcoming sales peak. With PSIwms AI in place, you can:

perform analysis of multiple warehouse operations scenarios in a short period of time

analyze various "what if..." scenarios

identify bottlenecks by visualizing warehouse traffic volumes

model new processes in a digital copy of a real-life warehouse (Digital Twin)

select optimum parameters of logistics processes based on multi-criteria analysis

use data from simulations to train ML algorithms for continuous optimization

Main areas of support

Complex optimization problems are solved using a set of advanced machine learning algorithms (known as BatchAI). Individual components optimize the process of matching orders with batch-es (for multiple orders processed simultaneously), use clustering techniques to for optimum goods reservation, and optimize picking paths through a CVRP algorithm.
Main areas of support
Selection of orders for batches

Selection of orders for batches

Create and compare best orders strategies for batches.

Make the most of existing logistics resources

Goods reservation

Goods reservation

Reserve goods optimally using advanced clustering.

Setting optimum picking paths

Setting optimum picking paths

Check the best order picking paths.

Coordinate people and resources.

Optimize your picking paths.

Where to deploy PSIwms AI?

PSIwms AI proved to be a best fit in an e-commerce warehouse, especially one involving a lot of manual processes, but it has a broad spectrum of applications.
Fulfillment Center 1

Fulfillment Center 2Fulfillment Center

Want to optimize your picking paths and arrangement of orders? PSIwms AI will propose most optimum picking paths or arrangement of goods. It will help you predict higher staffing requirements for rising order volumes.

Distribution Center 1Distribution Center

How to determine the impact of a new sorter or rearrangement of warehouse topology on pro-cess efficiency? PSIwms AI allows you to estimate the effects of potential or planned investments and changes. The user is informed whether a particular decision, e.g. pur-chase of a new sorter, will bring actual profits and how it will impact business operations.

Distribution Center 2
LPP Logo

Market leaders are already using AI

Thanks to the solution implemented, the length of picking routes has been reduced by up to 31%, as initial tests show. This also means a significant increase in the efficiency of the picking process itself.
Sebastian Sołtys, CEO of LPP Logistics

Project subsidized by NCBiR

FAQ - Questions and answers

What is PSIwms AI and how does it use artificial intelligence?
PSIwms AI is a comprehensive analytics platform that uses artificial intelligence to optimize intralogistics processes. It analyzes data from real warehouses, tests different solutions and optimizes logistics processes to make them more efficient.
In which types of warehouses does PSIwms AI work best?
PSIwms AI is ideal for e-commerce warehouses, especially those with a large number of manual processes. However, its applications are broad, including distribution centers.
What types of warehouse management support does PSIwms AI provide?
PSIwms AI supports warehouse management by analyzing warehouse potential, process optimization opportunities, and by testing and evaluating investments and new solutions using artificial intelligence.
How does PSIwms AI help in choosing a logistics strategy?
PSIwms AI helps select the best logistics strategy by assessing how potential changes will affect process efficiency. It uses advanced algorithms and artificial intelligence mechanisms to help make the right business decisions.
Does PSIwms AI require integration with a WMS?
PSIwms AI is integrated with PSIwms so that changes from the physical warehouse can be automatically transferred to the digital model and included in analyses. PSIwms AI uses data from the WMS - warehouse topology data to generate simulations and production data from the WMS (notifications/orders) to perform experiments/analyses.
What are the functions of the digital twin in PSIwms AI?
The digital twin in PSIwms AI analyzes various warehouse operation scenarios and provides recommendations for their improvement.
What are the benefits of using PSIwms AI?
The algorithms developed within PSIwms AI make it possible to reduce the cost of picking processes. Depending on the warehouse/assortment, they can increase efficiency by up to 20%. The larger the warehouse, the greater the benefit (in absolute terms, e.g. hours), but it will also be noticeable in smaller implementations. PSIwms AI implementation is possible in any warehouse regardless of size, e.g. to perform own experiments and analyses on the digital twin.
How can PSIwms AI simulate changes in the warehouse?
PSIwms AI makes it possible to simulate changes in the warehouse topology with high precision, check the impact of purchasing new equipment on efficiency, verify the ability of employees to handle sales peaks, analyze different work scenarios, identify bottlenecks, and model new processes in the digital twin.
What are the main areas that PSIwms AI supports?
The main areas of support offered by PSIwms AI include batch order selection, optimal goods reservation, and collection path optimization using advanced machine learning algorithms.
How does PSIwms AI support logistics decision making?
PSIwms AI supports logistics decision making by providing data-driven analysis, change simulation, and recommendations to evaluate the return on investment and logistics strategies, and to optimize logistics processes.

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You too can have a copy of your magazine for a test drive of its potential. Turn "What if... " into PSIwms AI!
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Piotr Picyk

Sales Director, Systems for Logistics and Public Transport


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