Hinduja Global Solutions is Developing Proprietary Generative AI Models
Generative AI holds significant promise for Indian IT firms. The top 10 IT companies in India are actively engaged in about 450 generative AI projects and Proof of Concepts (PoCs), indicating a strong commitment to harnessing the potential of this technology. Recently, AIM caught up with Partha DeSarkar, Group CEO at Hinduja Global Solutions (HGS), the IT management division of the billion-dollar Hinduja Group. He believes generative AI has the potential to significantly transform Indian IT, driving efficiency, personalisation, and innovation. “Generative AI can streamline and automate various IT processes, from code generation, testing, and IT operations to support leading and cost savings for businesses in India by reducing manual labour and improving resource allocation,” DeSarkar said. Moreover, HGS is developing its proprietary foundational models, which it will use for various internal and external requirements. “Unlike the OpenAI models, these will be specifically tailored to address specific client needs,” the veteran added. Leveraging GenAI for better CX HGS has gained extensive expertise in using AI for workplace safety, cognitive contact centres, and automation for the last several years. The IT management company has seamlessly integrated generative AI into its in-house cloud-based contact centre AI software called HGS Agent X. “Generative AI enhances the HGS Agent X knowledge base, enables instant AI responses for queries, aids call quality analysis to understand caller sentiments, and boosts associate performance. During chats, prompted responses can save associate time. AI helps draft messages, and associates ensure accuracy before sending them, thus optimising efficiency,” DeSarkar said. By leveraging the generative AI-powered HGS Agent X tool, a multinational financial corporation managed to overcome its struggles to read lengthy compliance statements aloud to customers accurately. “HGS has introduced HGS Agent X Smart Response to automate the process. This has decreased job stress for the financial corporation’s associates and boosted customer call satisfaction. In just four months, impressive outcomes have emerged — a 66% decrease in sales compliance errors, complete elimination of disclosure statement misreads, and a 49% increase in incentive payouts.” The Bengaluru-headquartered IT company adopts a hybrid approach, which means it uses industry standard LLM models and proprietary ones internally built for specific situations. HGS’ innovation labs located in Bengaluru and New York focus on bringing the benefits of LLMs in the most efficient and suitable way for its customers. “At our labs, we’re building internal generative AI models for internal use and clients, along with leveraging third-party platforms such as OpenAI’s GPT Models and open-source models like LLaMA to develop solutions. These models are used to solve specific internal and client-related problem statements.” Using generative AI internally Moreover, DeSarkar adds that his company, which operates a global network of customer experience centres across multiple countries, including the US, Canada, the UK, India, etc., is also using generative AI internally. HGS is exploring ways to integrate generative AI to make its existing HR solutions more efficient and relevant. “These include ‘Fit Index’, which helps us understand which clients/candidates are the best fit for us, and ‘Early Warning System’, which identifies unhappy employees or those likely to leave,” he said. Moreover, the company is also building models for intelligent document processing to glean content from multiple input sources. Tackling Challenges in GenAI Adoption While generative AI benefits enterprises, DeSarkar also stresses that carefully considering ethical, privacy, and regulatory aspects is crucial to harness the benefits while mitigating potential risks and challenges. “The use of AI in handling sensitive customer data necessitates robust data privacy and security measures to protect against breaches and misuse. Integrating generative AI into existing CX systems and workflows can be complex and require significant development effort. Some legacy systems may not be designed to accommodate AI technologies seamlessly,” he pointed out. Furthermore, hallucinations in LLMs is one problem the industry has yet to solve. According to DeSarkar, HGS’ models are being trained on comprehensive datasets, minimising hallucinations by exposing them to various scenarios. “HGS filters training data meticulously to eliminate bias, misinformation, or inappropriate content, reducing the risk of harmful model-generated output. We also employ strict privacy measures like differential privacy and encryption during data handling to safeguard sensitive user information during training and inference.” The company even incorporates human reviewers and moderators to evaluate and filter the content generated by AI systems, especially in critical areas like content moderation and news generation. “We have also developed ethical AI guidelines and principles that emphasise responsible AI use, transparency, and accountability.” Training Workforce in Generative AI In the age of generative AI, ensuring their workforce is well-versed and equipped to leverage these technologies is critical for companies. At HGS, according to DeSarkar, the company identifies employees with the potential to excel in AI-related roles and offers them opportunities to upskill or reskill for these positions. “We have developed a clear career progression path for such employees to then transition into AI-focused roles. We also plan to provide our people with training programmes and courses on generative AI, ranging from online courses to in-house training sessions. We also encourage employees to pursue certifications in relevant AI fields, such as data science, machine learning, and natural language processing.” Additionally, the company provides its employees access to AI tools and resources for experimentation and learning. This includes access to cloud-based AI platforms and software. “We are establishing mentorship programs, where experienced AI professionals guide and mentor employees who are new to AI,” DeSarkar concluded.
HGS is building foundational models in its labs in Bengaluru and New York
HGS is developing its proprietary foundational models, which it will use for various internal and external requirements.
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["data science", "GenAI", "machine learning", "OpenAI", "AI", "ML", "RAG", "Aim", "generative AI", "differential privacy", "Interviews and Discussions"]
["AI", "machine learning", "ML", "data science", "generative AI", "GenAI", "OpenAI", "Aim", "differential privacy", "RAG"]
I have a keen interest in creative writing and artificial intelligence. As a journalist, I deep dive into the world of technology and analyse how it’s restructuring business models and reshaping society.