Artificial intelligence and data analytics startup Ganit said on Tuesday it has raised funds from a group of investors and expects to double its workforce to 500 by the end of 2023.
The company did not disclose the amount of funds raised, but said the funding round was led by Sangeet Kumar, co-founder and CEO of Addverb Technologies; Krishnan Vishwanathan, co-founder and CEO, Kissht; Anshul Gupta and Amit Raj, co-founders of EatClub Brands (formerly Box8), among others.
“Ganit … raised an undisclosed amount in its pre-Series A funding round,” the company said in a statement, adding that it also plans to double its headcount to 500 by the end of this year. 2023.
Ganit was founded in 2017 by three data science industry veterans Shivaprasad KT, Ashok Harwani and Hariharan R.
“Watching organizational leaders struggle with the effective use of their captured data as well as their general reluctance to adopt analytics solutions, Ganit aims to make data consumable more than ever through actionable solutions, focusing on design and deploying purpose-built AI/ML (Machine Learning) to maximize decision speed and minimize decision risk across industries,” the company said.
The organization works with Fortune 1000 clients in the retail, pharmaceutical, consumer products and services, and BFSI (banking, financial services and insurance) industries across multiple geographies.
The new capital injection is expected to be used to expand its product portfolio in various areas including voice of the customer, forecasting, promotion planning, route optimization, price optimization as well as emerging growth areas fast, such as ESG (environmental, social and governance).
According to International Data Corporation (IDC) estimates, the AI (artificial intelligence) market in India is expected to grow at a compound annual growth rate (CAGR) of 20.2% over five years and reach 7.8 billion dollars in total revenue by 2025.
Industry experts also suggest that data science and AI could contribute up to $15.7 trillion to the global economy in 2030. This highlights the need for data-driven decision-making for businesses of all sizes.
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