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Ai2 Lab (Augmented Intelligence and Insights) allows rapid development from a concept prototype to data-driven business outcomes. The Lab can be leveraged to accelerate and test the feasibility of new use cases and innovative ideas before they are prioritized for implementation and scale-up.
Our approach is based on Dynamic Building Blocks, which allow solutions to be developed very rapidly, while being extremely agile and scalable.
The operational complexity and cost of knowledge-based “insights and prediction” generation from unstructured data is prohibitive for many life science organizations. Over 50% of the data originates and resides in the form of unstructured data, which can provide valuable insights for the organization, but the implementation is operationally challenging. When combined with structured data originating from business applications, the solution can be a game changer for the industry across the R&D, Clinical, and Commercial domains.
The capabilities can create a significant competitive advantage in the marketplace since every organization is figuring out innovative ways to generate insights and prediction from the similar type of data sources.
Ai2 platform enables the generation of “Intelligent Insights” by digitizing and integrating Unstructured + Structured data and leveraging cutting-edge Ai solutions that enable greater business outcomes by enabling prediction and insights. It is an integrated platform-based approach based on the concept of dynamic building blocks.
The Dynamic Building Block Approach accelerates the implementation of our 'Ai enabled Enterprise' vision for the organization based on a gradual evolutionary approach. RxDataScience hosts Rapid Data and Ai Labs that allow us to rapidly prototype and pilot targeted use cases in an agile approach before scaling.
This platform allows life science customers to aggregate their research information and data from other unstructured sources and different silos and formats them into a centralized location
Harness human-like Machine Learning to digitize data sources and generate the key foundational building blocks (metadata, named entity recognition, ontology, image recognition/classification, and entity relationships)
Revolutionize the way intelligence is derived from multi-document digitization and NLP solutions, tailored to the specific business requirements of the organization (eg, Therapeutic Areas, Clinical Domain)