Axilion
AI & Deep Learning software and SaaS for cities and transit operators.
| ILS | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|
| Revenues | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
| % growth | - | - | 40 % | (41 %) | 51 % | 16 % |
| EBITDA | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
| % EBITDA margin | - | (18371 %) | (1364 %) | (1725 %) | (1196 %) | (985 %) |
| Profit | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
| % profit margin | - | (18394 %) | (1415 %) | (1826 %) | (1266 %) | (1041 %) |
| EV | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
| EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x |
| EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x |
| R&D budget | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
| R&D % of revenue | - | 1429 % | 839 % | 1037 % | 932 % | 765 % |
Source: Company filings or news article
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Axilion is a technology company specializing in AI-driven traffic management solutions aimed at enhancing urban mobility. The company operates in the smart city and urban transportation market, serving municipal governments and city planners. Axilion's core product leverages advanced AI algorithms and Digital Twin technology to optimize traffic flow, reduce congestion, and improve pedestrian safety. The business model revolves around offering a hardware-agnostic software solution that integrates seamlessly with existing city infrastructure, thereby minimizing the need for costly upgrades. Revenue is generated through software licensing and service fees.
Axilion's innovative approach includes the use of AI Mobile Edge cameras to identify traffic issues and their root causes, and Deep Reinforcement Learning technology to continuously optimize mobility. The solution prioritizes eco-friendly travel modes and adapts swiftly to changing travel patterns, ultimately cutting travel time by up to 40% and reducing traffic-related emissions.
Keywords: AI, traffic management, urban mobility, smart cities, Digital Twin, congestion reduction, pedestrian safety, eco-friendly travel, Deep Reinforcement Learning, hardware-agnostic.