The nRoad team has developed solutions to extract, understand, and provide insights from unstructured data.
nRoad has introduced Convus, a platform that abstracts and incorporates unstructured data and documents into vital business functions. According to the company, unlike other horizontal NLP platforms and services, Convus is purpose-built for financial services with deep domain-centric machine learning models. The platform requires minimum training samples, enables faster deployment, and is built on a microservices-based architecture that can integrate with existing IT infrastructure in a non-intrusive way while maintaining required data security.
As unstructured data volumes keep spiraling out of control and the complexity grows, manual-heavy robotic process automation (RPA) requiring extensive human interaction and generic, one-size-fits-all NLP solutions are no longer viable. The nRoad team seeks to solve this problem and has developed solutions to extract, understand, and provide insights from unstructured data.
“Misconceptions about how unstructured data automation can be done have persisted for decades. This is a deep and domain heavy function that requires an understanding of what data is being presented, why it’s in a certain format, and how users want to consume that data. While in stealth mode, we carefully analyzed and identified some of the key challenges and developed our proprietary Convus platform,” said Aashish Mehta, CEO, nRoad.
The Convus platform allows financial institutions to extract, normalize, and incorporate critical business information buried in unstructured documents into mission-critical business processes. It offers a purpose-built enterprise-grade platform that delivers scale, accuracy, and efficiency with minimal training burden, reducing costs and avoids manual data extraction and entry; deep learning models adapt to changing document formats and structure.
