From data to advantage: Ecologic revolutionizes fleet management for global brands

Key project elements

Ecologic is an advanced SaaS system that transforms the way vehicle fleets are managed, combining driving style analysis, gamification, and artificial intelligence. Implemented in organizations such as Unilever, PKO Leasing, or Philip Morris, it enables precise monitoring of driver behavior and generates measurable benefits in terms of safety, fuel consumption, and operational efficiency. Through the integration of telemetric data and personalized feedback, Ecologic not only improves fleet management but also realistically changes the driving culture within organizations.

About the client

Ecologic.io is a dynamic technology startup offering an advanced fleet management system that combines safety, ecology, and corporate social responsibility. The company was founded after winning the Startup Fest Agora 2014 competition, and today it serves clients in Europe, Asia, and North America, supporting them in the digitalization and automation of fleet processes. Ecologic.io has achieved a leading position among providers of comprehensive fleet software in Poland, regularly presenting its solutions at industry conferences and in fleet media.

Initial requirements

At an early stage of development, Ecologic.io faced the challenge of finding a technological partner to help translate an ambitious product vision into a scalable and reliable enterprise-class solution. After a series of conceptual tests and initial pilot implementations, the startup needed a team that not only understands the complexity of Big Data projects but can also design an architecture capable of handling hundreds of thousands of telemetric devices operating in real-time.

In the first conversation with the development team, the client clearly emphasized that they expected a strategic partnership, not just code execution. The startup needed advice on technology selection, cloud architecture (AWS), the telemetric data processing model, and how to ensure business continuity with a growing number of users and vehicles.

As a result, a product-technology partnership was launched, aimed at building a stable and scalable fleet platform from scratch – ready to handle data from thousands of vehicles in real-time and serve as a foundation for Ecologic.io’s further development in international markets.

The Challenge

The biggest challenge in the Ecologic.io project was the scale and throughput of telemetric data generated by OBD2 devices. Each vehicle connected to the system continuously transmitted a massive amount of raw data — including speed, engine RPM, acceleration, braking, fuel consumption, diagnostic errors, and GPS position. With hundreds of thousands of active devices, the number of events was measured in millions of records per day, placing exceptional demands on the Big Data architecture.

A key indicator of the project’s success was for the system to be able to interpret and present the most important conclusions about driving style and the driver’s route to the fleet manager in less than 1 second, regardless of whether a single trip or data from several months was being analyzed. This meant the need to develop efficient data aggregation and indexing algorithms capable of instantly processing large volumes of information while maintaining analytical precision.

An additional challenge was synchronizing data arriving with delays, incomplete, or corrupted, which is typical for telemetric environments based on GSM networks. Devices installed in vehicles transmitted data at different frequencies and under various network conditions, requiring the use of anomaly detection mechanisms, packet validation, and automatic reconstruction of missing data fragments.

Project goals

Together with the Ecologic.io team, a set of key technological and business goals was defined to ensure a competitive advantage and enable global product growth.

Technological goals:

1. High performance and scalability – designing a Big Data architecture capable of processing millions of records per day while maintaining a response time of under 1 second for analytical queries of any time range.
2. Resilience and data consistency – implementing mechanisms for automatic validation, reconstruction, and synchronization of data transmitted with delays, in incomplete form, or corrupted during transmission from OBD2 devices.
3. Advanced analytical layer – developing models aggregating data on driving style, routes, and vehicle technical parameters, allowing for the generation of real-time insights.
4. Security and regulatory compliance – ensuring full compliance with GDPR and implementing multi-layered data security in transit and at rest (encryption, authorization, audits).
5. Flexible cloud architecture – utilizing AWS infrastructure with automatic scaling, data replication, and performance monitoring, enabling global system availability.

Solution description

The team designed a complete, scalable ecosystem for Ecologic.io to process telemetric data from thousands of vehicles in real-time. The AWS-based architecture enables the analysis of millions of events per day and the interpretation of results for the fleet manager in under 1 second.

Data from OBD2 devices goes to a central cloud, where it is automatically validated, cleaned, and synchronized — even in cases of delays or transmission gaps. The system uses Machine Learning to identify driving style, anomalies, and generate personalized recommendations for drivers.

The application layer includes:

• A web panel for fleet managers (React + SignalR) with full analytics and reporting,
• Mobile applications for drivers (Kotlin, Swift) with individual driving style scores and gamification elements.

The system has been secured with multiple layers (AES-256 encryption, GDPR, ISO 27001 audits) and operates in a SaaS model, with automatic scaling and continuous deployment of new features (CI/CD).

The result is an environment capable of ongoing interpretation of telemetric data and presenting key decision-making information in a fraction of a second — regardless of the number of vehicles in the system.

Results and business effects

After 10 years of development and work in a production environment, Ecologic.io maintains reliability at a 99% SLA level, handling data from hundreds of thousands of vehicles in real-time. The system has been repeatedly audited by independent pentesters, confirming a high level of security and GDPR compliance.

The platform analyzes over 800 types of road events, using Machine Learning algorithms for classification, driving style assessment, and risk forecasting. Key operational data is interpreted in less than 1 second, allowing fleet managers to make immediate, fact-based decisions.

Measurable effects of implementations include:

• reduction in the number of claims by 84%,
• decrease in fuel consumption by 1.1 l / 100 km,
• increase in driver engagement thanks to the reporting and gamification system.

Ecologic.io is today a stable and scalable fleet platform, combining Big Data analytics, machine learning, and the highest security standards in one ecosystem.

Client testimonial

From the very beginning, we wanted a partner who would not only fulfill our technical requirements but also help us build a product capable of global scaling. The team we worked with brought immense value, from designing the Big Data architecture and UX to data security