TRACTIAN
Tractian is the Industrial Copilot for maintenance and reliability, combining hardware and software solutions to monitor asset performance, manage industrial operations, and implement predictive maintenance strategies. Its AI-driven platform empowers businesses to prevent unplanned equipment downtime and boost production output. The company is headquartered in Atlanta, GA, and extends its presence globally with offices in Mexico City and Sao Paulo. Learn more at tractian.com.
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RaimaDB
RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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BrainBox AI
BrainBox AI employs advanced self-adapting artificial intelligence to enhance the efficiency of some of the largest energy consumers and greenhouse gas emitters: buildings. A significant yet often overlooked source of this energy consumption is the Heating, Ventilation, and Air Conditioning (HVAC) systems in these structures. Remarkably, HVAC systems account for 45% of the energy used in commercial buildings, with approximately 30% of that energy typically wasted. By leveraging deep learning, cloud computing, and our unique methodologies, our AI engine optimizes HVAC systems in real-time, delivering substantial benefits in energy efficiency, carbon emissions reduction, and overall building performance. As commercial buildings contribute significantly to global greenhouse gas emissions, our innovative technology has the potential to cut these emissions in half. Ultimately, BrainBox AI's transformative approach harnesses sophisticated algorithms and cutting-edge technology to make a meaningful impact in the fight against climate change.
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energyControl
energyControl is an innovative self-learning system designed to enhance indoor climate comfort while simultaneously minimizing energy usage, functioning continuously throughout the week. Our advanced artificial intelligence technology effectively reduces carbon emissions and energy consumption from HVAC systems by over 20%, all without requiring any manual input from operators. This solution allows for a seamless upgrade of existing buildings, making it an ideal choice for diverse environments such as offices, retail spaces, hotels, universities, and various other commercial establishments. The interactions among technical systems in larger buildings tend to be intricate, influenced by numerous factors that dictate specific energy needs. By connecting these elements, AI improves data streams through predictive analytics and learns the operational patterns of both the building and its HVAC systems. At any moment, energyControl can adjust the energy output according to the building's current occupancy levels and upcoming weather conditions, ensuring optimal efficiency and comfort. This adaptive approach not only supports sustainable practices but also enhances the overall management of energy resources in commercial properties.
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