Ottometric
Adriana Repac is a manager with over 15 years of experience in administration, finance, operations, and human resources. From 2012 to 2020, she held the position of Deputy General Manager at a five-star hotel Prezident, where she was responsible for day-to-day operations, interdepartmental coordination, service quality improvement, and team leadership. In 2020, she transitioned to the IT industry, joining Fiscal Solutions as a Finance and Administration Specialist. There, she gained valuable experience working in an international environment, managing financial compliance, reporting, and supporting internal processes. Since 2022, Adriana has been serving as the Legal Representative and Director at Ottometric's office in Serbia, overseeing all non-engineering aspects of the business—including legal, financial, and administrative operations. She also plays a key role as Head of People, leading the company’s HR strategy, employee development, organizational culture, and talent management. Adriana holds a Bachelor's degree in Economics and is currently pursuing a Master’s degree in Finance, Banking, and Auditing. She is known for her structured approach, leadership skills, and ability to align people and processes within dynamic organizational environments.
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Ottometric
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Ottometric provides analytics and enhanced capabilities for the automotive supply chain to understand challenges in ADAS features being delivered in modern vehicles. As vehicle complexity increases with more sensors and systems, the complexity and interdependency of the data fusion makes validation ever more complex, time consuming and expensive. The Ottometric solution provides simplified data management and visualization for this overwhelming deluge of validation data and our proprietary artificial intelligence (AI) and computer vision automates validation data review. The result is significant cost reduction and higher accuracy than manual review of data that utilizes in-house tools or unscalable off-the-shelf software. With more extensive and rapid data analysis, long tail problems can be better understood, further improving ADAS features being delivered to the market.