Predictive Solutions for Different Sectors of Logistics
In Summary
Transmetrics is a predictive optimization company which helps cargo transport companies and logistics service providers to be more optimal through the use of modern technology such as artificial intelligence (AI), data mining, predictive analytics and computer optimization.

Step 1 - Data Cleansing, AI Enrichment & BI Reporting
Transmetrics connects with your TMS system, auto-extracts the data on a daily basis, and improves data quality automatically with the help of AI. The software improves data quality issues such as missing events, values, and dimensions, as well as duplications and outliers. As a result, you get detailed historical reporting on operational performance and the ability to detect trends and target inefficiencies.
Step 2 - Business Optimization Modeling
Transmetrics calculates the most optimal way to use your resources based on the cleansed historical data, service levels, business requirements, and real costs. As a result, you get an optimized plan that can be used for strategic decision-making. This step also allows for shipment/customer/lane profitability reports as well as what-if scenario building.


Step 3 - Predictive Resource Optimization
At this step, Transmetrics incorporates forecasting into the optimization model. The software generates a daily rolling forecast of upcoming shipment volumes on the granular level per origin-destination. The forecasting window can vary from 1 day to several weeks, depending on your planning process and needs. The forecast is based on the cleansed historical data as well as a set of external factors (e.g. public holidays, seasonality, weather, etc.). As a result, you get an optimized dynamic plan to run the entire operational process days in advance. Depending on the business, the software suggestions help planning managers to precisely determine whether to decrease or increase capacity, use their own fleet or subcontractors, where to reposition assets, etc.
Step 4 - Execution controlling
In the last step, transport companies can monitor how the optimized plan was implemented and whether there were any deviations from it.

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NetMetrics
to increase cargo vehicle capacity utilization (mainly for groupage businesses when operating on their own network) - by providing high-accuracy forecasts of upcoming shipments and a daily predictive optimization of the linehaul network. -
AssetMetrics
to increase assets utilization (for assets owners including shipping lines, intermodal and asset rental companies) - by forecasting upcoming peaks in demand and suggesting the optimal storage, resupply, and maintenance strategy for assets. -
WareMetrics
to optimize human resources within warehouses (mainly cross-docking) - by forecasting upcoming shipments to a warehouse and optimizing labor shifts and shipments handling in advance. -
Technical Requirements:
Big Data and predictive analytics are complex concepts. That’s why our experienced team made the process of integrating and using Transmetrics as easy as possible for our clients.
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Historical data
At least 6 months of historical data (e.g. shipment measurements, tracking information, vehicle movements, etc.) -
VPN connection
We automatically extract data on a daily basis to provide you with the most accurate forecasts for your company. -
That's it!
Transmetrics is a Software-as-a-Service (SaaS) solution, so all hardware and software is provided by us on a monthly subscription basis.

Proven Record
Transmetrics tool helped companies save up to 25% of the linehaul costs, significantly increasing their profits as well as capacity and asset utilization.
Additionally, here are the results from the Proof of Concept projects:
For one of the pilot customers, the biggest cargo company in the world, Transmetrics made a prediction of future shipments with high-level accuracy – over 90%.
Data-driven simulations for another pilot customer (one of the Top 50 global freight companies) show that for groupage network, Transmetrics’ prediction enables a reduction of empty space within vehicles from 43% down to 18%. Such a reduction would potentially increase their profit by 300% annually.
Another pilot customer, with Transmetrics’ prediction, could achieve a 25% reduction in empty container logistics, which would equal approximately EUR 3 million in savings annually.
Pricing
Our pricing follows a monthly subscription model, which eliminates huge upfront investments and allows even medium and smaller-sized transport companies to benefit from our solution.
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Step 1 - Data cleansing and enrichment
The issue that many transport companies have is that their data is not clean so they don't have process transparency. They don't understand their actual efficiency and because the data is generated at multiple points and entered by people, the data quality cannot be easily improved at source. What we do instead is we invest in artificial intelligence algorithms which can look at the data, identify the issues and improve the data quality to the level where the significant transparency on the businesses is gained. -
Step 2 - Demand forecasting
Make this information predictive so not to focus primarily on historical performance but instead turn it into talking about future performance. In that process, we build forecasts for what the demand and supply will be for the next few weeks. This enables companies to visualize the problem areas while they are still in the future and they can be corrected by proactive action. -
Step 3 – Optimization
This step is about helping the planners and dispatchers in making decisions based on the forecasted information. The software can help you with suggestions on where to increase or decrease capacity in order to be very efficient and this is done with artificial intelligence and complex stochastic optimization algorithms. -
Step 4 - Execution Controlling
In the last step, transport companies can monitor how the optimized plan was implemented and whether there were any deviations from it.

The project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 945610.