Two years ago, IT consulting and services company Marlabs introduced its first Experience Centre in Yelahanka, Bengaluru, marking a milestone in the company’s expansion plans in India. Since then, the country has become one of the key markets for the company. Now, Marlabs is aiming to make India the centre of excellence for its AI products.
“Though headquartered in the US, Marlabs truly has its heart and soul in India. This Indian nexus is not just a physical presence; it’s where the energy and dynamism of our company are most palpable,” Thomas Collins, chief executive officer, Marlabs, told AIM during his recent visit to India.
India is poised to be the epicentre of AI initiatives at Marlabs, staffed with specialists equipped with the necessary skills and tools to oversee AI projects from start to finish, ensuring they are grounded in a strong foundational process.
“It’s here that we’ve established our centre of excellence, focusing on data engineering, analytics, and digital product development services. This strategic decision is rooted in our heritage, our talent pool within the company, and the rich external talent market in India,” added Collins.
About 75% of the company’s employee base is in India and it plans to add at least 500 more employees in a year.
The company’s hiring strategy is multi-faceted. It is looking for individuals with a blend of consultative skills – a mix of technology and business acumen. “Additionally, data science expertise, specifically in developing algorithms and data engineering, forms the crux of our talent acquisition. The focus is on building solutions for our clients, which requires a spectrum of skills from consulting to technical expertise,” added Collins.
The Marlabs’s data science team addresses a range of industry challenges, emphasising tasks like extracting insights from extensive datasets and employing pattern recognition, prediction, forecasting, recommendation, optimisation, and classification.
In an earlier conversation with AIM, Sriraman Raghunathan, digital innovation and strategy principal, Marlabs, said that the company’s hiring process for data science roles in India touches upon parameters like technical expertise, practical application, and experience.
It involves clear role definition, thorough job descriptions, technical assessments, AI/ML expert interviews, and HR interviews to ensure candidates are not only technically proficient but also fit well with the company culture and collaborative environment.
Growth Strategy
Since assuming the leadership role in October, Collins has articulated a clear and ambitious vision for the company’s trajectory in AI and ML. The goal is to double the company’s size within three years.
“Central to this vision is the integration of data engineering and AI as key drivers of revenue, aiming for these areas to contribute about 50% of the company’s total revenue,” said Collins.
The strategy to realise this vision is twofold. First, there is a focus on organic growth, which involves nurturing and expanding the company’s existing resources, skills, and capabilities in AI and ML. Second, since the primary focus for the next three years will be on life sciences and healthcare, Collins emphasises the importance of strategic acquisitions as a means to accelerate growth.
This includes its recent acquisition of Indianapolis-based AI consulting firm Onebridge which specialises in data engineering and analytics in the life sciences sector. Marlabs is currently working with four of the top ten global life sciences companies.
Another important aspect of our strategy is differentiating ourselves as a service provider, primarily through our company culture. “We believe in offering a great experience to both our employees and clients. It’s not just about the skills we possess but also about how we engage with our clients. We’ve received positive feedback about our approach and aim to further enhance the client experience,” Collins added.
AI & Analytics Play
Marlabs’ AI and ML operational efforts have covered a variety of projects. These include demand forecasting, inventory optimisation, linking point of sale data, evaluating admission candidates, detecting anomalies in real-time operations, and identifying irregularities in clinical trial reports.
“Generative AI is a game-changer, and we’re tackling it from two fronts: client solutions and internal applications. For our clients, we’re building industry-specific AI frameworks, using open-source technologies to maintain independence from major tech giants,” said Collins.
An example of this approach in action is a project the company undertook for a major telecom client, which enhanced its operational efficiency. Internally, the team is exploring the potential of generative AI to improve software development and increase efficiency in various support functions, including finance, HR, and marketing.
The team is also delving into generative AI for tasks like extracting and summarising knowledge bases in areas such as IT service desk ticketing, sustainable finance, medical device management, and rare disease education.
However, the key challenge lies in managing the quality of client data. Effective implementation of generative AI often requires significant preliminary data engineering work to ensure the data is properly harmonised and curated. “This has been a growing focus area for us, especially since the rise of generative AI has highlighted the need for more robust data strategies,” concluded Collins.
Read more: Data Science Hiring Process at Marlabs
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