HCLTech drives business ops and experience with live GenAI

The announcements of new generative AI (GenAI) initiatives multiply by the day, but HCLTech has remained a quiet early adopter, delivering real case studies with tangible outcomes.

The firm was an early customer for the Microsoft/Open AI co-pilot at HCLTech and Google DuetAI/Github co-pilot at HCL Software. It set up GenAI labs drawing on expertise developed in its international Cloud Native Labs to lead its efforts. HCLTech is in the launch partner program for all the major hyperscalers for GenAI.

While much of the market is just embarking on the GenAI journey, HCLTech has proven cases with value delivered, built on two decades of co-creating AI technologies.

Private LLM saves time for healthcare workers and delivers a better patient experience

In healthcare, HCLTech developed a large language model (LLM)-powered medical conversational agent that generates tailored responses to patient queries. So far, it has resulted in 40% time savings for healthcare workers, and its prepared summaries for physicians have improved patient experiences through swifter treatment.

HCLTech built a private model utilizing an open-source and commercially available LLM. It generates text messages based on the context of patient answers (known as conditional prompting) and uses these answers to complete a form capturing the patient’s health information, summarizing the conversation for health professionals to refer to easily.

It’s a clear example of using GenAI to speed up a business process and enhance patient and employee experience.

GenAI enhances design engineer capabilities for a global automotive maker

As enterprises began their early exploration of GenAI, HCLTech became the innovation consultant to a global automotive company to identify and optimize designs for the best effect in the real world. HCLTech recommended no-code AI software to aid designers in generating new designs and assist with live prediction of how the designs would perform.

HCLTech inspired the automotive giant with use cases:

• Verifying engineering designs without building physical prototypes
• Predicting workflow using 3D deep learning, providing models for volumetric data
• Executing uncertainty quantification and probabilistic modeling to help understand how models will behave in varying scenarios

To achieve these use cases, HCLTech developed an innovation ecosystem encompassing avant-garde global startups powered by AI software and algorithmic platforms, along with startups offering machine learning-based design simulation software.

HCLTech builds better processes from its sales data

A third HCLTech case study illustrates how it can apply existing data to create new insights. It is also an example of the firm drinking its own champagne. In this case, HCLTech’s LLM technology supports and enhances its sales processes. Team members can ask natural language questions about company sales data ingested from across the business and gain on-the-fly insights at their point of need.

The process uses a retrieval augmented generation (RAG) technique, where data is ingested from source documents, the text chunked up for storing, and insights retrieved via a Q&A agent. The agent has custom tools that enable users to retrieve semantically similar documents depending on the user’s question. Similar documents are identified and uploaded to the LLM in an improvement cycle, enhancing answer quality over time. This approach removed aggregation, analysis, and reporting generation steps from an equivalent but much slower manual business process.

Together, the cases support HCLTech’s view that business operations optimization is the area of IT service activity with the greatest initial applicability for GenAI. But it is also true that employees’ capabilities are enhanced in each case described—an outcome HFS believes enterprises should prioritize as they set their GenAI goals.

The Bottom Line: GenAI is live and in action, so get started on enhancing business ops with a focus on helping your people deliver better outcomes.

GenAI solutions are well and truly off the drawing board and in live action in the wild. Business operations emerge as a practical starting point. But when considering optimizing, be sure to place the benefit for the humans engaged front and center to realize GenAI’s true advantages. Before you rush ahead, to avoid nasty surprises, you must be disciplined in governing consumption to understand and manage costs as usage scales.

Watch out for our generative enterprise services Horizons report, due soon.

Further reading

• The dos and don’ts and potential costs of generative AI
• How business leaders can take control of the GenAI conversation