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Hevo Data Secures $ 1 Million in Start-up Financing to Streamline Data Integration

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Moving from food delivery to data integration may seem like an unlikely progression for a start-up team, but it was a natural fit for the founders of Hevo Data. Manish Jethani and Sourabh Agarwal have already launched SpoonJoy, an on-demand restaurant delivery application in India. The challenges encountered in analyzing the data to improve the service of SpoonJoy inspired them to form Hevo Data, a cloud-based data integration platform that has just raised 1 million start-up funds led by IDG Ventures India.

Hevo Data's chief executive, Jethani (Agarwal is its chief technology officer), says SpoonJoy, whose investors include SAIF partners, had to analyze data from many sources. For example, if the volume of orders began to fall in an area, the team would look at web and ad traffic, engagement and customer feedback, as well as the activity of competing services. This meant that they had to use the data from Google Analytics, Mixpanel, Zendesk or Salesforce, which had to be organized and formatted first. This process is time consuming and, without a data integration platform, small and medium businesses can only analyze the data once or twice a week.

"One of the challenges of food delivery is that data must be highly optimized," Jethani says. "Food margins are very low, so if your delivery cost is high, you will not earn money. So we built a lot of technology to optimize the logistics part of things. We come from a very strong experience in engineering and data and we wanted to solve the food delivery with data. "

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SpoonJoy was purchased in 2015 by Grofers, one of the largest grocery delivery services in India. Afterwards, Jethani and Agarwal worked for a year at Grofers before founding Hevo Data, which has offices in Bangalore and San Francisco.

Jethani explains that Hevo Data's solutions can reduce the time needed to prepare data in minutes. One of the reasons why companies enroll in data integration services is to prepare the data for machine learning algorithms, because these algorithms are only good for their data d & # 39; learning. Hevo Data does not target specific industries, but its typical customers are small and medium-sized businesses with engineering teams of fewer than 400 people, which means they have to make sure that the scientists and engineers spend most of their time developing algorithms. ideas about the data instead of organizing it.

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"It took us a long time to gather the data before we could start the analysis, which is very inefficient if several people are busy cleaning up and bringing in data. instead of analyzing them, "says Jethani." If we can reduce the cycle from a few weeks to a few minutes, we can respond more quickly to business needs. "

This is especially important for companies that need to analyze the data as soon as they get it, such as on-demand food delivery services (Swiggy, the most important service of food delivery in India). Hevo Data is cloud-neutral, so users can use it on any cloud platform they use, including Amazon AWS, Google Cloud Platform, and Microsoft Azure. It also offers an on-premise version of its platform for large companies with a private cloud.

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Hevo Data, which will use its seed to recruit more engineers and expand in the US, is competing with other data integration companies like Informatica, Pentaho and Talend. Jethani says that the advantage of Hevo Data is that it is native to the cloud and therefore better equipped to handle data in real time.

"More and more things are happening in real time, so our architecture is designed to handle real-time data that flows quickly," says Jethani.
In a statement, the executive director of IDG Ventures India, Venkatesh Peddi, said: "Today, companies are investing heavily in technology to strengthen and empower their data teams in order to obtain a competitive advantage in their space We invested in Hevo Data because we saw a strong team building an excellent product that fills a significant gap in the market. "

Featured Image: John Lund / Getty Images

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