Augmented intelligence for logistics
Logistics assets like shipping containers are expensive to store and expensive to move, yet 1 in 3 of them is moved empty, costing €18B/yr. This leads to increased CO2 emissions and lower margins for logistics companies. The underlying problem is knowing day-to-day cargo demand and predicting how it might vary based on holidays, weather, seasons, market fluctuations, and more.
Our expertise is predictive analytics for logistics. Global consulting firm Roland Berger places us in the fast-growing ""Booking & Optimization Platforms"" sector. Our competitive advantages include an advanced AI-based data cleansing stage which lets us use real-world low-quality data.
Our tools help cargo companies to increase their operational efficiency, cut carbon, and reduce costs through
1) demand forecasting (based on historical data and external factors) and 
2) predictive asset use optimization (shipping containers, railcars, trucks, etc).
Our first-generation product, NetMetrics for large companies, required manual installation and hand-tuning. Pilot customer DPDgroup recorded a 14% increase in capacity utilization. 9% fewer trucks were on the road, as per new EU CO2, NO2 and particulates emissions reduction targets.
After a successful Phase 1 application, our feasibility study showed need for this EIC Transmetrics project for midsize clients:
•	Develop predictive asset management functionality 
•	Aggregate logistics data of multiple companies to bring the statistical certainty of large numbers to forecasts for our mid-sized clients. 
•	Aggregate relevant external databases to improve forecasting 
•	Simplify the adoption of our system with try-before-you-buy ease, for quick scaling
•	Productize data-cleansing stage to allow faster sales cycle and scale-up
Transmetrics, our next-generation product, will bring similar efficiency improvements to mid-sized logistics companies, which account for 30% of the transport industry.
We plan to reach €+32M revenues by 2024.