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How we made
saving people possible

517 people were injured or killed in level crossing accidents in the EU in 2017. Erriate was built to prevent these accidents.

What have we
built?

We developed special algorithm for video recognition and built the hardware infrastructure that make the analysis feasible in the real time.

Employees of the railway company can approach the footage archive. Emergency units can monitor dangerous situations or accidents at the level crossings.

The mobile application warns train operators about risky situation on the level crossing they are approaching and provides them with livestream.

What the process
looked like?

Analysis of
the current state

In case of railway accidents, we found that activities pursued by railway companies does not reduce the number of accidents. Therefore, we figured it is necessary to build something reactive. That’s how the Erriate was created – as a supplement to campaigns that raised the awareness regarding the responsibility at level crossings.

The model
needs training

We recorded hundreds of hours of video capturing various objects and situations. This helped us create and train the algorithm in order to achieve desired precision. However, the process does not end here. The employees can still evaluate the riskiness of the situation marked as “dangerous” and, therefore, support the accuracy of the model.

Go live
and evaluation of the results

When everything was ready, we decided it was time for the physical installation of the system. We ensured everything was properly set so it can work seamlessly, along with the appropriate training and manuals for employees. The next step is to evaluate how many accidents Erriate was able to prevent…

Used technology

17
Team allocation

How AI boost
the revenues of airline carrier

Bulgaria Air is the national air carrier of the Republic of Bulgaria. The company’s main objective is to offer its customers services of the highest quality on board its new, safe and comfortable aircraft, and to constantly improve its product.

What have we
built?

Air Bulgaria were able to determine how sales and demand will change over time. This helped them adjust the number of seats available, prices and operation costs in order to maximize revenue and profit.

Based on the customer segmentation, we were able to predict the potential of customer and adjust the price of the ticket. By doing so, we were able to increase the propensity to purchase and maximize the revenue.

We created an algorithm that assigns individuals into clusters based on their behavior or sales potential. This helped the company to understand the buying nuances of their customers and adjust the offers accordingly.

Used technology

13
Team allocation