TIGER ANALYTICS: Roaring through AI consulting

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When we think of AI and consulting, our minds often drift to the usual suspects: Europe, the United States, or China. After all, companies like Accenture, founded in Ireland, and IBM, with its roots in New York, have long been at the forefront of AI, ML, and consulting innovation. These regions remain the epicenters of cutting-edge technology and strategic advising. However, every so often, a trailblazing firm emerges—one that not only challenges the status quo but also taps into an overlooked market. Enter Tiger Analytics, a company founded by two visionary Indians. Their mission? To revolutionize the consulting game while staying deeply connected to their roots. Despite being headquartered abroad, Tiger Analytics embodies the spirit of returning home, creating a global success story with Indian ingenuity at its core. This case study tells you the story of Tiger Analytics. So, let’s plunge in!

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As usual, let’s start with a little history about the company. 

The Beginnings

Tiger Analytics was started in 2011 by Mahesh Kumar and Pradeep Gulipalli. It is a testament to the transformative power of data analytics. The company began as a small team of 10 data scientists and engineers, operating from Silicon Valley and Chennai, with a mission to address complex business challenges through advanced analytics. Both founders brought complementary skills to the venture: Mahesh Kumar, an academic with expertise in operations research and statistical modeling, identified a market gap in data-driven decision-making, while Pradeep Gulipalli’s technological acumen enabled the development of cutting-edge machine learning solutions​.

What made Tiger Analytics unique is that it’s value proposition lied in its ability to provide customized solutions at scale. Leveraging in-house frameworks and codified algorithms, the company reduces costs and development time significantly. For instance, it successfully built a predictive maintenance system for a North American railroad company, reducing unnecessary costs associated with damaged sensors. In another instance, Tiger Analytics created a robust data governance framework for a logistics firm, improving gross margins by 2.5%​.

The company’s culture emphasizes innovation and trust. Even during periods of economic uncertainty, Tiger Analytics maintained its hiring momentum, fostering employee loyalty and positioning itself as a leader in the AI talent market. Additionally, the company has embraced generative AI, aligning its offerings with market demands and technological advancements. This approach ensures employee engagement with cutting-edge projects while meeting client needs​. 

From cub to a Tiger: TAs’ growth phase

After 2 years of running and building a foundation, 2013 proved to be the turning point for the firm. Tiger Analytics got their first formal office and also landed their first major client who is a fortune 500, semiconductor manufacturer. The company’s problem was to improve sales effectiveness and this was taken care of by tiger analytics. The rest of the growth journey looks like this:

• 2014 – The company started focusing on elements it could build: an ML engine capable of predicting future technological changes and a recommender engine for suggesting news articles. It is important to remember that these technologies were in their infancy at the time, and the demand for them was still largely untapped. However, it was clear that the company aimed to specialize in deep analytics and pattern recognition through machines, which lies at the core of machine learning. Another important tool developed by Tiger Analytics was their NLP reserve. NLP stands for Natural Language Processing. These tools are highly effective in analyzing various language-related data from humans and prove invaluable in applications such as virtual assistants.

• 2015 – Tiger Analytics continued to expand its capabilities. From equipment maintenance and personnel safety to sports training, the company began serving a diverse range of industries. Along the way, they received several lucrative buyout offers but chose to stay independent, firmly believing in their vision and potential.

• 2016 – The Data Engineering department received increased focus, as it plays a critical role in supporting machine learning algorithms. During this period, the company also concentrated on consulting and curating tailored analytics solutions, strengthening its position as a leader in data-driven decision-making.

• 2017 – The company began developing its Accelerator strategy—building blocks of reusable code designed for rapid deployment. Alongside this, it established the Tiger Academy, a dedicated initiative to empower employees and clients through specialized training programs, further solidifying its expertise in analytics and machine learning.

• 2019 – 2020 – Both years saw significant progress in Tiger Analytics' functionality as the company expanded into ML Operations (MLOps) and its related applications. This marked a critical shift towards enhancing the operationalization of machine learning models. When the pandemic struck, forcing teams to work remotely, Tiger Analytics seized the moment to contribute to AI-for-good initiatives. These projects supported governments and NGOs, leveraging AI to improve decision-making, resource allocation, and community services during a time of global crisis.

After a meteoric rise, Tiger Analytics is now focused on strengthening its global presence. The company is renowned for its intellectual properties, with TigerML standing out as a key offering. This platform enables businesses to seamlessly implement machine learning solutions, streamlining complex processes. In addition to its international footprint, Tiger Analytics has remained deeply rooted in India, with offices in Chennai, Hyderabad, Bangalore, and plans to expand into Bihar, demonstrating a strong commitment to its origins.

To the present: Current standing of the company

It’s 2024 and Tiger Analytics has evolved into a global leader, partnering with over 100 clients, including Fortune 1000 companies, across sectors like retail, healthcare, financial services, and manufacturing. With a team of more than 4,500 professionals spanning five continents, the company delivers AI-driven solutions that empower businesses to embrace intelligent automation and drive transformation at scale. Below are some more amazingly exceptional numbers that will surprise you to no end about a company that probably might have never even heard of:

• As of late 2024, Tiger Analytics reported an annual revenue of approximately a whooping $750 million, with aspirations to reach $1 billion within the next five years, driven by increasing demand for AI and analytics services from enterprise.

• Tiger Analytics has been recognized as a Leader in various industry assessments, including the ISG Provider Lens for Retail Specialty Analytics Services and the Everest Group’s PEAK Matrix for Analytics and AI Services Specialists. This recognition underscores its capabilities in delivering advanced AI-driven solutions tailored to specific industries.

• The estimated revenue per employee at Tiger Analytics is around $308,000, indicating a strong productivity level relative to its workforce size

Market Position

In comparison to the other firms in the industry, Tiger Analytics’s revenue places it among the most notable competitors. For instance:

• Fractal Analytics: $1.47 billion revenue

• Tredence: $756.9 million revenue

• ZS Associates: $3.79 billion revenue

Tiger analytics has been recognized for its rapid growth, being listed among the Inc. 5000 fastest-growing companies with a growth rate of 543% over three years, ranking it at No. 933 in 2024.

In conclusion, Tiger Analytics is a testament to how Indian talent can thrive on the global stage in AI and analytics consulting. By prioritizing innovation and offering tailored solutions, the company has steadily carved out its space, challenging industry giants. At the same time, its commitment to staying connected to its roots—both culturally and geographically—adds depth to its success story. As it scales new heights, Tiger Analytics is set to keep shaping how businesses use data to make smarter decisions worldwide.

This is the story of Tiger Analytics and how continues to grow. While it does that, let’s take a look at the lessons any entrepreneur, working in AI space or even outside this space, can learn: 

Business lessons

1. Go Niche, and grow outwards – Its does not really take a rocket science degree to understand that operating in a niche market is one of the best strategies to grow your company. Operating in a lean model and serving a small base of customers helps you refine your products & services. Tiger Analytics did the same by by tailoring solutions for sectors like retail and healthcare, and investing in AI tools like NLP and TigerML, they’ve built customized, scalable solutions. This strategy of niche specialization and rapid deployment helped them and still continues to do so to deliver impactful results and stay ahead of the competition.

2. Leveraging Cultural Roots for Global Success: While Tiger Analytics is headquartered abroad, it’s deeply connected to its Indian roots. This includes its commitment to setting up offices in Indian cities and tapping into the talent pool. While it is not really a business lesson, embracing your cultural identity and leveraging it as a strength when expanding globally can provide you with a unique perspective and operational advantages.

That brings us to the end of this issue. I really hope you like it. If you did, share this within your network, and I will give you a special shout out with your message in my next issue. Don’t miss this chance to appear in front of an audience of 1600+ subscribers.

I will get back to you with more stories like these. In the meantime, take a look at these other interesting case studies:

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Keep tuned for more such case studies.
Until then,
Happy Reading!