Virtusa Helio: Revolutionizing Generative AI Adoption with Practicality, Innovation, and Responsible AI Practices

CXOToday has engaged in an exclusive interview with Ram Meenakshisundaram, Chief Technology Officer, Virtusa Corporation

1. Can you provide an overview of Virtusa Helio and its key features? How does it differentiate from existing GenAI platforms in the market?

Virtusa Helio is a comprehensive suite of services and tools developed by Virtusa, aimed at helping businesses harness the power of Generative AI (GenAI). Designed to drive real-world applications and generate tangible business benefits, Helio is positioned as a catalyst for achieving enterprise AI at scale. The suite is crafted to deliver practical solutions that enhance productivity, drive innovation, and keep organizations competitive in their respective industries.

Key features of Virtusa Helio

• Engineering-first approach: Ensuring practical and effective implementations, making AI an integral part of existing workflows to provide solutions that work in the real world is a core promise of Virtusa Helio.
• AI-first approach: Virtusa Helio is rooted in GenAI technologies. For a business at the beginning of its GenAI journey OR for a business deeply immersed in GenAI, Virtusa Helio offers tailored solutions to meet its needs.
• Driving innovation: Accelerating outcome by enhancing productivity and fostering innovation, it is designed to keep businesses competitive by leveraging cutting-edge AI technologies.
• Ecosystems and accelerators:
  • Helio Innovate: An ecosystem built to fuel ideation, explore GenAI use cases, prioritise them basis relevance and build solutions.
  • Helio Build: An array of tools developed to accelerate greenfield development using the power of GenAI.
  • Helio Enhance: Utilizing GenAI to accelerate the modernization of legacy systems, Virtusa Helio optimizes workflows and processes, ensuring sustained innovation.
  • Helio Operate: By integrating GenAI and AIOps, Virtusa Helio establishes intelligent operations by automating complex use cases to deliver unprecedented efficiency.
• Expert guidance: With a team of 200+ AI architects and 1100+ GenAI engineers specializing in neural networks, deep learning, prompt engineering and fine tuning, Virtusa ensures that businesses receive top-notch guidance throughout their GenAI journey.
• Responsible adoption: Virtusa Helio emphasizes responsible adoption, ensuring compliance, mitigating risks and unlocking human potential through ethical AI practices.

Virtusa Helio is designed to be flexible and adaptable, fitting into current ways of working and intersecting existing human workflows with GenAI interventions. This approach makes the assets extensible and highly customizable for both Ai assisted engineering and business solutions. Early successes include a large global bank using Virtusa’s Helio Enhance solution to accelerate a large modernization effort by embedding it into their existing methodology. This approach is rooted in understanding client needs and providing grounded, relevant, and dependable advice on generative AI. Virtusa Helio’s differentiation lies in its practical, real-world applications, tailored solutions, and emphasis on responsible adoption, making it a unique offering in the GenAI solution market.

2. Can you elaborate on the development process behind Virtusa Helio?

The development of Virtusa Helio was deeply rooted in understanding client needs and the evolving landscape of generative AI. Following the advent of ChatGPT in November 2020, we engaged in extensive conversations with ~300 clients to identify their problem areas and understand industry trends. These discussions revealed four key areas where generative AI could be highly effective: business process automation, model assurance, Greenfield and Brownfield projects, and automation opportunities.

Based on these insights, we developed Helio, a brand designed to address these specific needs. Helio consists of four key offerings: Helio Innovate, Helio Build, Helio Enhance, and Helio Operate. Helio Innovate focuses on developing generative AI applications, providing the necessary ecosystem for infrastructure, partnerships, and tailored solutions. Helio Build caters to Greenfield and Brownfield projects, ensuring effective application of generative AI. Helio Enhance emphasizes improving and fine-tuning existing AI models, while Helio Operate leverages generative AI to drive efficiency in automation.

Our approach was not to make a marketing splash but to provide grounded, relevant, and dependable advice on generative AI. This strategy resonated with clients, leading to the creation of the Helio brand. The name ‘Helio’ was chosen from ten different options, symbolizing the sun’s dual connotations: illuminating the path forward for clients and marking the dawn of a new era of innovation.

The Helio brand helps align our internal initiatives across talent, capability, offerings, solutions, accelerators, and delivery, ensuring consistency with our identity. In the short term, it aids in quick client recall of our generative AI focus. Over time, we aim for Helio to be synonymous with relevance and dependability, a responsibility we are committed to upholding.

3. How does Virtusa Helio address the unique needs of different industries? Could you provide specific examples of how the platform has been tailored to solve industry-specific challenges?

Organizations benefit from AI adoption in several ways: automation of routine tasks and integration of AI in IT operations enhance efficiency and productivity. AI-driven insights enable informed decision-making and fosters strategic growth. AI workflows optimize processes across functions, boosting agility and scalability. Virtusa supports these initiatives with strategic guidance, solution development from inception to execution and ongoing assurance to ensure performance and compliance. Virtusa Helio is designed to support the entire lifecycle of AI adoption across multiple disciplines and business functions.

Some of the early successes where Virtusa Helio has demonstrated its effectiveness includes:

1. Warehouse management optimization àA leading information management services company was heavily reliant on manual inspections for physical record identification and re-boxing damaged items. This was turning out to be a highly cumbersome, time-consuming, and inefficient process. With Virtusa Helio, we developed a GenAI enabled drone detection system for warehouse management. In this, the drones mapped the site, identified damaged boxes using AI-driven navigation and vision models and automated the re-boxing requests. This system achieved 30 times faster scanning and 80% accuracy in damage identification, significantly reducing inventory management costs and improving operational efficiency.
2. Enhancing case management for an insurance organizationà A global insurance organization’s existing case management system was inefficient due to manual email reviews and no unified view of case history. This resulted in increased handling time and decreased productivity. Virtusa implemented a case management solution by leveraging Pega’s GenAI capabilities for automated email summarization, action item identification and data privacy compliance. This solution optimized specialist’s efficiencies thereby reducing case research time by more than 80%, increased agent’s productivity and enhanced accuracy and consistency in case handling.
3. Project management assistance for a professional organizationà A globally recognized professional organization for project management had their project managers struggling with project failures, were facing data relevance issues and had a lack of effective tools, leading to significant time and resource wastage. Virtusa implemented a GenAI assistant using sophisticated LLM models and enabled project managers to access reliable information, generate documents and receive smart recommendations. The implementation of this AI assistant helped achieve 99.4% accuracy rate across their projects, increased efficiency by 60% and reduced manual efforts by 70-80% thereby supporting global adoption and empowering decision-making.

Through these innovative AI solutions and Helio, Virtusa has demonstrated its ability to drive AI-led transformation and deliver exceptional value to clients by enhancing their operational capabilities and giving them the competitive edge.

4. How do you address concerns related to the reliability and accuracy of generative AI outputs? What measures are in place to mitigate common issues like hallucinations?

We have developed a comprehensive framework, called Helio Assure, to validate GenAI output of our clients’ enterprise apps. It follows a four-step validation process. The first step involves validating the source Data corpus, which could comprise of both structured and unstructured data, where we check for issues like skewness, duplicates, toxic content etc. This check is useful for GenAI systems that use Retrieval Augment Generation (RAG) for business context. Second step is to validate the Prompt Injections to ensure prompts are secure, concise and free from bias. Additionally, we are building prompt templates for domains such as banking and insurance, which can be applied for frequently asked questions and popular transactions to minimize deviations. The third step is to validate the Response itself, which gets further classified as an Answer, Generated Content, Insight or Summary. Different validations are applied based on the Response classification. For instance, if the Response is an answer to a question (which is given as a prompt), the most important checks are to determine the accuracy and relevancy of the Response. To achieve high level of accuracy, we have to ensure sufficient and representative ground truth data, verified by the SMEs, is created as reference. Where ground truth is missing, we leverage another baselined ‘LLM as a judge’ and look at how closely its output matches with the production GenAI system output. If the similarity score exceeds the threshold, the Response is sent to the end user. As a fourth and final step, we seek feedback from the end user, which can be in the form of like/dislike or a rating. Based on the feedback, we conduct further analysis and take corrective action, which could mean Fine-tuning the model or updating content in the corpus.

We believe the above iterative process involving continuous validation and refinement, forms a virtuous cycle that significantly enhances the quality of GenAI output over time. Further, as our initial pilots with select clients show, Helio Assure framework leveraging Retrieval Augment Generation (RAG) with a high ‘Faithfulness’ setting, significantly reduces the probability of hallucinations.

5. Can you discuss some of the major trends and shifts in AI adoption by enterprises in India?

In India, several major trends are shaping AI adoption among enterprises. Generative AI is set to significantly impact business operations, with its potential to revolutionize content creation, simulations, and personalized customer experiences. By 2024, this technology is expected to drive substantial innovation and efficiency.

AI-driven automation, such as Robotics Process Automation (RPA), enhances accuracy and reduces costs by automating repetitive tasks, allowing employees to focus on strategic work. Advanced analytics and predictive insights improve decision-making by providing actionable intelligence from large datasets, enabling better trend forecasting and customer understanding. Natural Language Processing (NLP) and conversational AI enhance customer service through chatbots and virtual assistants, offering personalized experiences and greater efficiency. AI in computer vision and image recognition boosts quality control and expands applications in sectors like manufacturing and healthcare. In cybersecurity, AI strengthens defenses by identifying patterns and anomalies in real-time. AI’s integration with IoT devices through Edge AI enhances real-time decision-making and operational efficiency. Additionally, adopting ethical AI frameworks ensures fairness, transparency, and builds trust.

These trends indicate that AI is driving significant changes in how businesses operate, helping them scale, reduce costs, and enhance customer loyalty. By leveraging AI, Indian enterprises can gain a competitive edge, innovate more rapidly, and improve overall business agility.

6. What are the current challenges businesses face when integrating AI technologies?

Integrating AI technologies into business operations presents several challenges. Issues with data quality and management are prevalent, as AI systems require vast amounts of accurate and consistent data. Many businesses also lack robust IT infrastructure and face a shortage of skilled AI professionals. The complexity and cost of integrating AI with existing systems lead to uncertainties about ROI.

Data privacy and security are significant concerns, particularly when using commercial large language models (LLMs) that require sending sensitive data to third-party services. This exposes businesses to risks if data is not adequately protected. While self-hosting LLMs can mitigate these risks, it may be cost-prohibitive. Additionally, LLMs’ “black box” nature complicates transparency and accuracy, posing challenges for compliance and customer trust.

Ethical concerns, regulatory compliance, and cultural resistance to change further complicate AI integration. Scaling AI solutions across different departments also adds to the complexity.

To overcome these obstacles, businesses need a strategic approach that includes investing in infrastructure, training employees, managing change effectively, and committing to ethical AI practices. By addressing these challenges, businesses can successfully integrate AI technologies, driving innovation and achieving their strategic goals.

7. How do you foresee the evolution of AI technology influencing business strategies over the next five years, particularly in the Indian market?

As we look ahead to the next five years, the evolution of AI technology is poised to profoundly influence business strategies, particularly in the Indian market.  The immense potential of AI to enhance human capabilities and drive growth across industries will feature critical and emerging technologies essential for India’s growth trajectory.

Enhanced Personalization and Customer Experience: AI will drive deeper personalization across industries. Businesses in India will increasingly leverage AI to deliver tailored experiences, predict customer preferences, and optimize interactions. This shift will require advanced AI solutions to analyze vast data and provide actionable insights, ensuring competitiveness in a rapidly evolving market.

Operational Efficiency and Automation: AI will continue to streamline operations by automating routine tasks and optimizing processes. Companies will adopt AI-driven solutions to enhance productivity, reduce operational costs, and improve decision-making. These efficiencies will be crucial for businesses aiming to scale effectively.

Innovation and New Business Models: The growth of AI will spur innovation, leading to the creation of new business models and revenue streams. Indian businesses will explore AI-driven products and services, transforming traditional industries and creating new market opportunities. Capabilities in generative AI will be instrumental in facilitating this innovation and helping businesses adapt to the latest trends.

Data-Driven Strategies: With the increasing importance of data, AI will become central to developing data-driven strategies. Businesses will utilize AI to gather insights from complex datasets, forecast trends, and make informed strategic decisions. Advanced analytics and data processing capabilities will support Indian enterprises in making smarter, data-informed choices.

Ethical and Responsible AI: As AI technology evolves, there will be a growing emphasis on ethical AI practices. Businesses will need to ensure that their AI systems are transparent, fair, and aligned with regulatory standards. Solutions designed with ethical guidelines in mind will promote responsible AI usage.

India’s robust adoption of AI is driven by its commitment to technology-driven innovation and positive transformation. Key factors include strong government support, such as the substantial funding allocated to the India AI Mission, aimed at developing AI infrastructure and fostering workforce skills. Enhanced IT infrastructure and continuous technological advancements further facilitate widespread AI deployment across industries.

Despite this momentum, Indian enterprises face significant challenges in terms of AI adoption. These include concerns about infrastructure and connectivity, data quality and availability, ethical and regulatory concerns, cultural and organizational resistance, and education & awareness.

Overall, the evolution of AI technology will lead to more sophisticated and strategic approaches in business operations. By leveraging advanced AI solutions, Indian businesses will be well-positioned to navigate these changes and harness the full potential of AI to drive growth and innovation.

8. What are the common barriers to AI adoption that enterprises in India face?

Enterprises in India, while on the AI adoption spree, are facing some barriers. However, with a few strategic efforts, these can be effectively managed. Some challenges that they are facing, at present are:

Inadequate infrastructure and connectivity is perceived as one of the largest challenges for AI adoption. Especially for small and medium-sized enterprises (SMEs), the infrastructure is not uniformly available, but ongoing improvements in infrastructure present a positive trend. Data quality and availability also pose issues, as AI systems require large volumes of high-quality data, which many enterprises strive to access and maintain, highlighting an opportunity for enhanced data management solutions.

Ethical and regulatory concerns, including data privacy and bias in AI algorithms, add another layer of complexity. However, addressing these concerns by developing transparent and fair AI systems can significantly enhance trust and compliance with regulatory standards.

While AI adoption has increased rapidly over the years, there are a limited number of skilled AI professionals in India. The gap between understanding AI technology and its benefits to business leaders and employees can be bridged through education and training programs essential to building AI literacy and skills within organizations.

In India’s competitive business landscape, the initial investment for AI infrastructure, software, and talent are being looked into, with a close lens, as on today. However, the long-term benefits and potential for growth make these investments worthwhile. Integrating AI solutions with existing IT systems and workflows can be complex, but the opportunity to streamline and enhance business operations outweighs the cost of investment.

Addressing these challenges will take some time in the India market but once the opportunity value is realized, Indian enterprises can leverage AI’s transformative potential to drive innovation and growth like never before.

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