Brodmann17
Deep-learning Engine for Visual Recognition
Company Overview
Snapshot
Founded in November 2016 by Adi Pinhas, Amir Alush, and Assaf Mushinsky, Brodmann17 operated with 1–10 employees. The company raised a total of $19.39 million across 5 funding rounds from 9 investors. In December 2022, Brodmann17 ceased operations.
Business overview
Brodmann17 developed vision-first technology for automated driving, leveraging a lean, patent-pending software architecture to deliver high accuracy with minimal computing power. Its deep-learning vision solutions were designed for the automotive industry, targeting OEMs and Tier 1 suppliers. The company specialized in artificial intelligence, machine learning, and computer vision, operating within the Automotive & Mobility Technologies sector.
Strategic signal
Brodmann17 ceased operations in December 2022, resulting in the layoff of 30 employees. This event signals a significant downturn for the company, indicating a failure to sustain its business model or achieve profitability despite prior funding and technological advancements in the automotive computer vision space.
Company Intelligence Q&A
- What is Brodmann17's primary focus?
- Brodmann17 focused on developing deep-learning vision technology for automated driving, providing solutions that offer high accuracy with low computing power for the automotive industry.
- When was Brodmann17 founded and by whom?
- Brodmann17 was founded in November 2016 by Adi Pinhas, Amir Alush, and Assaf Mushinsky.
- What was the outcome for Brodmann17 in December 2022?
- In December 2022, Brodmann17 ceased operations, leading to the layoff of 30 employees.
- Which investors participated in Brodmann17's March 2019 funding round?
- In March 2019, Brodmann17 received funding from investors including iAngels and UL Ventures.
- What was a key technological advantage of Brodmann17's solution?
- Brodmann17's technology utilized a patent-pending software architecture that enabled state-of-the-art accuracy in deep-learning vision while consuming only a small fraction of computing power, making it suitable for various automotive applications.