Environmental Compliance Monitoring, Energy Monitoring Solutionautomated utility monitoring and management solutionsOur in-situ/handheld super data collectors capture every agri-environmental parameter at custom configured intervals, which would enable our customers to take recommended actions in real-time!building autonomous systems for commodity/crop life cycle intelligencebuilding geoanalytical decision engines that are self learning and predict potential risks to provide appropriate recommendations across various value chainsbuilding systems that trace the commodity value chain in real-timebuilding global knowledge base for commodity/crop life cycle intelligencebuilding systems that trace carbon-emissions and its impact in real-timeempowering the customers with the right set of tools to monitor, verify and trace commodity value chains in real-time.self-learning autonomous systems that alert customers in advance.geographic trail of commodity, consumption, supply and demand predictions for the market placeWe are a team of scientists/researchers, technologists, architects, designers and programmers who are uniquely qualified with exceptional skill sets acquired over number of years in academia and industry.We are backed by industry leading mentors and academicians.We are supported by Founder Institute, Google (Grants)We are supported by some exceptionally creative minds from top tier institutes who moonlight for this vision.Now agri-environmental indicators at your finger tips. receive alerts, recommended actions and predict potential scenarios in real-time. SycliQOne platform empowers the customer for custom configuration of alerts. Subscribe now to learn about a whole world of functionality at your fingertips. REAL TIME DATA DRIVEN DECISION ENGINEERING Plan, Research, Trail/Track, Verify, Compare, Predict/Forecast, Model commodity/crop life cycle intelligence using real-time data from hyper-local sensing platform. Our team of scientists/researchers are constantly working on autonomous solutions for unforeseen scenarios. We understand all aspects of data, and when we add a geographic- dimension to it, potentials are huge.
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