Artificial Intelligence and data science provide several promising benefits that include, and are not limited to, complex pattern detection, forecasting, decision making capabilities and low turn-around time to adjust for new market changes. As the computational infrastructure is becoming more powerful, faster and cheaper, AI is being applied in several areas including fintech.
Our approach just does not stop with the above benefits. We strive to take next big and important step by performing real-time AI calculations and then display the live analytics using interactive graphs on smart devices. This ensures that our customers are more empowered and have fewer external dependencies for the information when they need it most. In addition, we provide several automated features that helps them in adjusting and managing their investments.
We are developing centralized as well as blockchain based decentralized system to support financial and digital economy. Please request a demo or our business models to know specifics.
SignoFi application is offered on android and iOS based smart devices. At present SignoFi is in its beta testing phase with fully developed android as well as iOS applications. SignoFi applications and corresponding business models are available for demo.
Yes, we would be happy to share our case studies with you. Our case studies covers test results from all business days in the year of 2021. Please send us a request for case studies if you wish to review them.
SignoFi application is currently offered in two versions. First supports stocks and second supports digital assets/NFTs. Both the versions are is scalable to the product derivatives.
SignoFi application is can be integrated with any financial trading market across the globe. For real trading configuration, a partnership with local brokerage firm is required. For digital assets, our system provides complete platform without a dependency on external broker.
SignoFi is designed to be used as both a Business to Business and a Business to Customer application, and to be available based on the needs of each member of the financial market.
By design, Artificial Neural Networks(ANN) have a memory of past events, and they can be used for breaking down complex input pricing data into patterns for classifying trade signals and trend generation. The ANN approach ensures very low turnaround time for training the neural networks to adjust for any new market changes. The implementation details are available in our system document.
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