No matter your industry, organization or job role, digital technology is most likely transforming it right now.
Going Digital can deliver improved customer experience, increase employee productivity, wring out service inefficiencies, safeguard infrastructure, strengthen the brand and ensure a competitive edge. These digital experiences serve to unlock information and provide a more integrated and contextual view in order to give enterprises a more complete understanding of customers and transactions and enable better-informed decision making.
And building a Digital Enterprise Means involves Transformational Shifts in journey to a service 4.0 to reinvent products and services from design and engineering to manufacturing and support, accelerating operational efficiency and enterprise-wide growth.
Only a fraction of business have realized the full impact of their digital investments, enabling them to achieve cost savings and create growth. The optimal mix of technologies could save companies hugely.
The traditional value chain will pivot toward hyper-personalized experiences, products and services driven by innovative business models that result in new sources of revenue.
This transformation is already underway, but not proceeding at the same pace everywhere. Also, there is huge inequality in the penetration of digital change across industries. While in some there were core changes due to digitization, in others the impact of this phenomenon was limited to minor or secondary changes.
The key challenge however, is the complex legacy technology is the chief barrier to digital transformation, requiring adaption or replacement of existing infrastructure to accelerate digital transformation.
We crunch and digest data with our strategic understanding of the outcome needed and with our AI capabilities (specifically around Natural Language Processing) around large datasets. From country-level health data to predict illness outcomes to financial data to improve credit scoring, Zencode is able to further your goals.
We have strong capabilities in creation of Natural Language Processing (NLP) engines for use in unstructured big data understanding.
From data pre-processing and filtering to feature extraction and classification. We create our own Convolutional Neural Network (CNN) to process the text in a hierarchical manner for different use cases