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Automated AI-based inventory management for logistics

Project description

Using computers to count crates

Crates and pallets move thousands of goods and other loads across all countries and continents around the world. For inventory managers, the ability to locate each and every pallet or crate is vital. This is mainly a manual and labour-intensive task that is also prone to error. The digitalisation of freight transport and logistics is the next big move. The EU-funded doks Innovation project is developing DigiLOGIS, an automated inventory management system that uses artificial intelligence (AI) to track the location and condition of pallets and crates in real time. This new system can count, find and verify the condition of goods stored. It replaces manual tracking as well as handheld scanner and manual measurements for master data gathering.


Industrial companies, large retailers anIndustrial companies, large retailers and logistics operators move thousands of crates or pallets loaded with
goods every day. Knowing where exactly every pallet or crate is in a large warehouse is the first priority of any inventory management system.
Logistics currently involves a lot of manual handling which is error prone, labour-intensive and slow. The growth in e-commerce and the increasing
digitization of industry (Industry 4.0) represent significant challenges but also opportunities for new technological solutions. Digital logistics
processes will be a vital to the digital company of the future.
DigiLOGIS is an automated inventory management system, which uses AI to track the location and condition of pallets and crates seamlessly and
in real time. The system counts, finds and verifies the condition of goods stored. The system consists of modules that are contionously capturing
and updating the inventory and master data to the Warehouse Management System (WMS). It replaces manual tracking, handheld scanner and
manual measurements for master data gathering. Initial prototype trials of individual modules at several large automotive, engineering companies
and two international logistics operators, showed that the technology prevents mistakes and improving accuracy of information, boosting
efficiency, just-in-time capabilities and reducing claims.
The ability to capture accurate master data is essential for doks' technology. The goals of this Phase 1 project are to conduct (i) a technical
feasibility study, will test the entire prototype solution, and its integration with enterprise software systems with trial customers (ii) a commercial
feasibility study to analyse and quantify the benefits of the solution at these trial customers and design an optimal go-to-market and scale up plan.
The Phase 2 project will optimise the current solution to full market readiness based on the technical and commercial findingsx

Call for proposal


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Sub call



Net EU contribution
€ 50 000,00
34131 KASSEL

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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Hessen Kassel Kassel, Kreisfreie Stadt
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Total cost
€ 71 429,00