C2RO Cloud Robotics

Based in Montreal, Canada, C2RO Cloud Robotics is a software-as-a-service (SaaS) firm that provides privacy-aware AI video analytics for physical environments. Founded in 2016 by Soodeh Farokhi, C2RO was incubated at Tandemlaunch Inc. In 2017, Riccardo Badalone, an entrepreneur with a background in building enterprise cloud computing companies, was appointed CEO, with Farokhi transitioning to the role of Chief Technology Officer. Badalone previously co-founded and led Diablo Technologies, a company in the high-performance enterprise memory and storage space. This experience in enterprise cloud solutions complements C2RO's focus on AI and cloud robotics.

The company's core business revolves around its AI-powered video analytics platform, ENTERA™, which leverages existing security cameras to provide insights into human behavior within physical spaces. This technology serves a diverse client base, including retail, shopping malls, smart cities, industrial facilities, and hospitality sectors. The business model is primarily subscription-based, offering solutions as a cloud service. C2RO generates revenue by helping businesses optimize labor, deter theft, and enhance customer experiences through data-driven analysis of foot traffic, customer journey, and operational efficiency. A key differentiator is the platform's emphasis on data privacy, ensuring compliance with regulations like GDPR by using biometric-free, faceless analysis.

The ENTERA™ platform offers a suite of features for detailed operational analysis. It can track visitor foot traffic, occupancy levels, and demographic data such as age and gender, all while protecting individual identities. For retailers, the system analyzes the entire customer conversion funnel, from pass-through traffic to in-store engagement and sales, providing metrics on dwell times and product interaction. This allows for A/B testing of store layouts and marketing campaigns. A specific application, ENTERA™ Theft Deterrence, integrates AI analytics with RFID technology to detect fraud and theft in real-time, particularly at self-checkout stations in fashion, grocery, and fuel retail. The platform is designed to be hardware-agnostic, integrating with existing RGB sensors and security cameras, and operates on a cloud-based infrastructure that processes data in real-time. The company has secured several rounds of funding, including a seed round of $1.1 million in 2018 and a Series A round of $2.25 million in 2019 to accelerate commercialization.

Keywords: AI video analytics, retail analytics, theft deterrence, loss prevention, customer journey mapping, occupancy monitoring, smart retail, GDPR compliant AI, computer vision, behavior analysis, business intelligence, SaaS, physical space analytics, operational efficiency, RFID fusion, asset protection, people counting, smart city solutions, data-driven retail, cloud robotics