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This data science and AI consulting company uses sophisticated tools and techniques to help organisations maximise their decision-making power.


Covid has revealed pain points in the past few months in several industries. Companies want to know more than ever now what will drive their business further. Rather than just a gut feeling, they are now looking for definite numbers that can point in a definite direction of success.

This is where data and analytics organisations are stepping in to provide those numbers and statistics that can help organisations make the right decisions. The Tech Panda spoke to Shivaprasad KT, the CEO and Co-Founder of Ganit Inc, a fast-growing data science and AI consulting company that designs smart solutions at the intersection of hypotheses analytics, discovery-based AI, and new data from IoT.

Shivaprasad KT

Shivaprasad KT

While there was a lot of craze in analytics, consumption of analytics was lacking. The only motivation for us to start Ganit was to actually flip this equation. We will start with consumption of analytics.

“I call ourselves a niche data science boutique kind of a company, which operates in an area not in direct competition to most of the companies out there. While some companies might be doing things similar to what we are doing, the DNA and the fabric of the solutions that we have built are actually quite different,” he says proudly.

Shivaprasad, who has spent close to 18 years in the data science industry, is passionate about what data can do for decision making.

How Ganit Inc Works

Established in 2017, Ganit Inc has worked with leading organizations across five geographies, India, the US, the UK, Middle East, and Southeast Asia. The startup has served projects for Fortune 1000 clients across industries, which include Fast-Moving Consumer Good (FMCG) or Consumer Packaged Goods (CPG), retail, logistics, hospitality, media, insurance, and Banking, Financial Services and Insurance (BFSI) industries.


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Ganit Inc uses sophisticated tools and techniques to mine big or small data emerging from transactions, behaviours, macroeconomic conditions, social interactions, IoT devices, etc. The solutions offered are based upon reporting and amp, dashboarding, inquisitive analytics, predictive analytics, and machine learning, which are easy to implement.

The startup uses BI, predictive analytics, and machine learning techniques in combination with products and services designed based on their deep industry domain expertise, to solve complex business problems.

Ganit Inc’s Philosophy

At the core, Ganit Inc is a data science and AI consulting company. Its consulting services result from two broad offerings, services and products. Currently, the company is over-indexing on services, while they have a strong strategy to push out AI products in the near future.

Shivaprasad explains that they offer broadly three services, the first of which is traditional hypothesis-based analytics, where a business knowledge-based hypothesis is proved or disproved based on data.

With the advent of big data and data deluge that has happened, we have the time, skill, and energy to hypothesise. And you need to let machines discover some hidden patterns that are otherwise not so apparent for many business leaders

“If you prove it, then you’re confirming your gut feeling, which is a good thing. Now it’s data driven, which is always better than pure gut feeling. If you’re disproving your hypothesis, it’s a new discovery for your business,” he explains.

The second part of their services is discovery-based AI. He explains that machine learning techniques can eventually give the AI power that informs of the trends that are worth pursuing.

“With the advent of big data and data deluge that has happened, we have the time, skill, and energy to hypothesise. And you need to let machines discover some hidden patterns that are otherwise not so apparent for many business leaders,” he says.

The third part is data from IOT and sensors, which is a new kind of data that has emerged because of advancement in IOT devices, sensors, and beacons. Shivaprasad compares this data to a new animal in the jungle.

“This new data is like the new animal of the jungle. Hardly anybody knows how to really tame this animal. It looks like a cheetah, is as mighty as an elephant, and as ferocious as a lion, but we don’t have a name for it. Ganit is trying to put a name for this data and integrate all new data in with the old data. That’s where the magic happens,” he says.

When we take a new project, we always ask the client, ‘If you have the best of my analytics, how will you consume this? What kind of decisions will you make?’

Ganit is helping customers to operate at the intersection of these three parts.

“You can imagine these three as the three vertices of a triangle, where we are helping clients to operate at the intersection, so that they can take advantage of all these three at the same time,” he says.

Ganit Inc’s Origin

The startup was founded by SP Jain’s alumnus, Shivaprasad, along with Co-Founders, Hariharan R, and Ashok Harwani. It was the lack of consumption of analytic solutions that prompted the creation of Ganit.

While consulting with senior CXOs in the US and Australia, Shivaprasad realized that about 90% of the analytic solutions created were not getting consumed. Many companies were putting money and time on building a dashboard under report, but seldom would they get consumed or implemented.

Another pain point he found was that people would build sophisticated creative analytics models, but the output was never made useful for the rest of the organization.


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“While there was a lot of craze in analytics, consumption of analytics was lacking. The only motivation for us to start Ganit was to actually flip this equation. We will start with consumption of analytics. When we take a new project, we always ask the client, ‘If you have the best of my analytics, how will you consume this? What kind of decisions will you make?’” he explains.

With Ganit Inc, they wanted to make consumption a reality and increase the consumption of analytics.

From a three-member team in 2017 to more than hundred strong in less than two and a half years, the startup is now aimed at building a 1,000+ resource sized company to be a leader in the analytics and AI space in the next three years.

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