Sensory AI

The Need
The Financial Market is notoriously volatile and unpredictable. Having a tool that can predict market movements with a high accuracy rate can be extremely valuable for traders. Moreover, the use of “Deep Neural Network” allows the system to learn and adapt to new market trends and patterns, making it a powerful and adaptable tool.

The Request
Why seek funding?
We are seeking funding to cover the costs associated with data collection and processing, neural network developpment and training, and system implementation and monitoring. Your investment will help us make The Sensory AI a reality.

The Plan
The Sensory AI will be implemented in several stages:
1- Data Collection: We will collect historical Financial Market data from various reliable source. This data will be used to train our “Deep Neural Network”;
2- Data Preprocessing: The collected data will be preprocessed to ensure that they are in the correct form to feed our neural network;
3- Neural Network Training: We will use a “Deep Neural Network” to model the data. It will be trained using a combination of historical and real-time data to predict market movements.
4- Testing and Validation: After training, we will test and validate the performance of our neural network.
5- Implementation: Once we are satisfied with the performance of our Neural Network, we will implement the system on a financial market trading plataform.

Development Goals
1- Functional Prototype: Our first milestone is to have a functional prototype of the Sensory AI in 6 months. This prototype will be able to analyze historical Financial Market data and make basic predictions.
2- Rigorous Testing: After the development of the prototype, we will spend the next 3 months conducting rigorous tests to ensure the accuracy the system’s predictions.
3- Beta Version Launch: After the testing phase, we plan to launch a beta version of the Sensory AI to a select group of users. The feedback from these users will be crucial to improving the system.
4- Official Launch: Our goal is to officially launch teh Sensory AI 18 months from the start of the project.

Implementation Plan
1- Data Selection and Preparation: We will collect historical Financial Market data from Various reliable sources. This data will include financial market indicators. The data will be preprocessed to ensure that they are in the correct form to feed our neural network. This may include normalizing the data and removing outliers.
2- Development of the Deep Neural Network: We plan to use a Deep Neural Network (DNN) to model the data. The DNN is a class of machine learning models that are capable of recognizing complex patterns in the data. We will choose a suitable DNN architecture based on the nature of our data and the problem we are trying to solve.
3- Training and Testing: The Sensory AI will be trained using a combination of historical and real-time data to predict market movements. During training, we will test and validate the performance of our neural network. This will allow us to adjust and optimize the model to improve its accuracy.
4- Implementation and Monitoring: Once we are satisfied with the performance of our neural network, we will implement the system on a financial market trading plataform. We will be abe to use the system and continue to monitor the system’s performance and make adjusments as necessary to ensure it continues to provide accurate predictions.

Financial Planning
The obtained financial will be allcated as follows:
1- 30%  will be allcated to system development, including the hiring of professionals in deep neural networks (if necessary) and software engineers.
2- 10% will be reserved for the testing phase, which includes the collection and analysis of financial market data(if necessary, the surplus of this resource will go to the testing stage).
3- 10% will be reserved for the testing operations.
4- 30% will be used for marketing and promotion od Sensory AI.
5- 20% will be kept as a reserve for contingencies.