Once we have identified the problem to solve, we would gather and prepare the data required to train the AI model. This may involve cleaning, transforming, and normalizing data to ensure it is in a suitable format for use in the AI algorithm.
Deployment & Integration
Once the AI model is trained and evaluated, we would deploy it into production. This may involve integrating the model into an existing system or building a new system around it. During deployment, we would consider issues such as data privacy, security, and scalability.