The importance of integrating AI with existing business functions and tools

Arun 'Rak' Ramchandran, President & Global Head - Consulting & GenAl Practice, Hi-Tech & Professional Services, Hexaware, talks about their GenAl solutions, LLMs, data, cloud, privacy, and sustainability.

- MINU SIRSALEWALA

How does Hexaware strategically align Generative AI capabilities with the specific business goals of its clients?

Hexaware strategically aligns GenAl capabilities with specific business goals by employing a structured approach, including understanding client needs, addressing challenges like bias, compliance, and data security, and fostering collaboration. Our approach focuses on creating customized use cases, prioritizing those based on feasibility, relevance, and Rol, and integrating AI with existing business functions and tools.

Our customizable GenAl services and solutions power optimal business operations and create seamless AI journeys. Through our consulting framework, Decode Al, and execution framework, Encode Al, we cover the entire lifecycle to ensure rapid deployment and maximum value creation for diverse industry needs. We're committed to disrupting ourselves, our clients, and industries by infusing GenAl into every aspect of service delivery.

How can organizations ensure data quality and traceability in GenAl solutions, and what methodologies maintain clear data lineage throughout the development lifecycle?

Ensuring data quality and traceability in GenAl solutions are paramount for reliability and effectiveness. At Hexaware, we advocate for a comprehensive approach to address these challenges.

Firstly, let's talk about data quality. We advise organizations to establish a robust data governance framework, clearly defining roles and permissions regarding data access and actions. Additionally, implementing data validation checks during data ingestion and processing is crucial to maintain accuracy, consistency, and completeness. We also ensure regular data cleaning processes to address any missing, incorrect, or irrelevant data.