Data is so relevant to business then ever due to evolution of business models based on data patterns , analytical models and deep learning. The essential problem scarce data usage against data abundance. Furthermore, the challenge is to ensure that the data used to train the system is representative and leads to reliable solutions. The current state of gaps comes with applying data collected for one purpose to solve a different problem, without making necessary allowances for gaps in dataset. We enables businesses think on how to apply this form of AI.
Intelligent automation will enable simplified digital process in a combination of human & machine. The approach to simplification majority times treat it as sophisticated technology without a true purpose. This creates higher complexity and resistance to unwind for a rapid change of business process and model. We realize the true form of simplification lies in understanding how businesses validates the need for simplification.
We offer the fit-for-purpose model with right technology interventions will be at the fore-front of technology adoption by enterprises as growth enablers.
As Human ignites the journey of collecting, cleaning , labelling and feeding data to train the machine learning systems, the joint forces will co-create value in improving the business. Learning will not be limited to technocrats but the business heads need to understand when the business problems are susceptible to a deep-learning approach and how to manage the technical teams with diverse skills to solve the business problem. We enable the training and education for organizational changes occurring in the co-existence of Human minds and AI minds.