ARTIFICIAL INTELLIGENCE IMPLEMENTATION
Artificial Intelligence (AI) performs a principal role in promoting productivity, efficiency, and clarity across industry segments and domains. At COGNXT, we implement a proven strategy and framework that transform enterprises and help them reap the benefits of machine-driven intelligence.
Data preparation is the most crucial step in the AI workflow. Without sound and accurate data as input to train a model, projects are more prone to fail. Training of an AI model starts with the process of precisely tagging data from various data sources. Our implementation experts focus on classifying input datasets, pre-processing data elements, and assuring correct tagging of the data as per the preferred model.
Once the data is cleansed and accurately tagged, we model the intelligence workflow and use the classified datasets to train the AI model. A well-planned modeling phase goes a long way in building a robust and reliable model that can deliver meaningful information based on the data.
Simulation and testing for accuracy are crucial elements that validate the accuracy of an AI model. Ensuring everything works well together, with other systems, before deploying a model into the real world. Before deployment, we reassure that the model will respond the way it is supposed to, no matter the situation.
Deployment is the last stage in the AI life cycle and can get clumsy with inexperienced hands. Through the deployment phase, our architects and data engineers work in tandem and progress the AI model through various deployment environments; while also ensuring that the model consistently delivers sensible business decisions based on data.