Building on the success of our drone-based project, we turned our expertise to camera feeds. We engineered a state-of-the-art analytics system that could handle vast amounts of data, evidenced by our processing of a whopping 31 terabytes for a single client within a year. Much like our drone project, this system was designed with a user-centric approach, providing operators with intuitive tools to derive insights from live feeds. Our commitment to efficient data processing and seamless user experience has cemented our reputation in the realm of real-time video analytics.

In collaboration with the DoD and SOCOM, our startup unveiled a cutting-edge prototype designed for drone positioning coupled with live data feeds. What sets our system apart is its intuitive no-code interface. This ensures that operators, even without a background in computer science, can swiftly deploy pipelines, achieving quick insights. By harnessing the power of Node.js, Python, and React, and being versatile with cloud services like AWS and GCP based on vendor preference, we've pioneered a solution that democratizes advanced drone surveillance, making it accessible and efficient.

Our team ventured into creating a unique Platform-as-a-Service (PaaS) specifically designed for logistics enterprises. This ERP solution is not just any platform; it's tailored for companies demanding sophisticated features like real-time asset management, integrations with inventory systems, and traffic insights. One of its crowning achievements is the self-hosted algorithm developed in C++ for optimal truck routing. Using a robust stack including Django, Redis, WebSockets, REST APIs, and Ionic, we've provided logistics firms with a comprehensive, adaptable, and powerful tool, setting a new benchmark in the domain of logistics management software.

I embarked on the challenging task of creating a computer vision algorithm in C++ with the support of OpenCV, specifically designed for lane drift detection in the realm of autonomous driving. Remarkably, this algorithm operates without the dependency on neural networks. Its precision lies in its capability to accurately pinpoint lanes, even under conditions of notable degradation. Employing a microservices architecture, the system seamlessly communicates with diverse peripherals. Our groundbreaking work not only advanced the field of autonomous driving but also captured the attention of prominent insurance companies, solidifying our startup's reputation in the industry.

In a strategic move to refine customer acquisition, I collaborated with a website owner to optimize their Salesforce integrations. Through a thorough analysis of the Salesforce CRM, I identified and rectified leaks in the sales pipeline, effectively funneling more potential customers. Simultaneously, I employed advanced SEO techniques on the website, significantly enhancing its visibility and organic reach. These combined efforts culminated in a commendable 23% reduction in customer acquisition cost, marking a pivotal success in cost-efficiency and operational excellence.