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Meet Tvarit, the startup that has developed an AI platform for sensor-data analytics. They are currently in the Evolve phase of EDI incubation programme, working on a solution for Migros data provider.

Can you tell us how you came to your Startup idea? We would also love to know more about your team, what makes your dynamic so promising and impactful?

Having entrepreneurial experience in the Manufacturing industry and professional experience in the analytics, Suhas Patel (CEO) and Rahul Prajapat (CTO) decided to bring a unique product for the manufacturing industry.

Suhas Patel has 15 years of experience in building startups, including starting 5 greenfield manufacturing factories. He has a bachelor’s degree in computer science from India and a master in Telecommunications from Paris. Suhas is an advisory board member and the past president of TiE Deutschland, one of the largest networks of entrepreneurs headquartered in Silicon Valley.

Rahul Prajapat, “The Passionate Technocrat”, is CTO at Tvarit GmbH. Rahul holds B.Tech and M. Tech degree from IIT Bombay. He is also a recipient of numerous prestigious awards including CAG by Hon’ble Prime Minister of India for creating ‘Promoting Research and Innovation’ plan, MIT GSW and Web Summit Dublin for technical leadership.

Apart from the founding team, Tvarit has a team of 18 people who are mostly data scientists who are dedicated to Tvarit’s vision to build, “Scalable Industrial AI Platform building Customer-centric use-cases”.

 

What makes your solution unique? What is the impact you are trying to achieve?

Tvarit has developed an industrial AI platform with 37 algorithmic modules from data extraction -> data engineering -> predictive modelling and visualization, while most companies are focused on predictive modelling. Many big companies who are in a similar business are having generalized solutions whereas we are very much focused on manufacturing sensor-data analytics. Our automated modules allow data-scientist to achieve more in less time and in a more efficient way.

Tvarit is aiming to be a market leader in Industrial AI solution with differentiated and customer-centric use-cases.

What challenge have you selected for the EDI incubation programme and why did you choose it?  

Tvarit selected Migros challenge to predict the impact of ambient conditions on customer basket size and customer behavior. Tvarit has worked on sensors-data in the past  and we are very confident about the solution we can provide to Migros. Moreover, Migros, being an innovative company, has a sizable data science team with whom we can discuss and learn more from.

For a few months you have worked hard in the EDI Experiment stage, developing your Big Data solution even further. Can you please elaborate on your progress and how have you evolved during the acceleration process? How was your experience working with your Data Provider? 

Throughout the Experiment phase, Tvarit was focused on delivering more value to Migros. In the first week itself, Tvarit was able to impress Migros by finding an anomaly very much related to their business. It used metadata like weather information, store location information to create more business value.

Due to the visibility we have gained with EDI, we could easily secure investment during the Experiment stage. We have increased our team size and expanded our solution by including more algorithmic modules.

Migros has always been supportive and easy-to-approach. They provided all the answers we required with good explanations. Many times, the Migros team helped us finding the business direction to understand their data better.

EDI allows the participants to work hands-on with real-world data, which is a possibility that startups rarely have

After joining and benefiting from the tools EDI provided you, what is your next step? 

We have identified and approached a few customers already, who have shown interest in our solution. We will be meeting them soon. We have recently closed the investment round and will be expanding the team in technology as well as in the area of sales. We discussed with a few customers who want to customize the solution and we have decided to focus on customization.

Finally, what would you say to a startup considering applying to EDI? 

EDI is the must-to-attend acceleration program, which provides data (to build solution), visibility (to attract customers and investors) and money (to finance the company). A data-science startup requires all three to accelerate. We got a great coach and a mentor during the experiment phase who helped us by walking an extra mile with us in guidance, offering help in meeting customers and helping us not lose our focus.

Liked what you read?

EDI 3rd Open Call is coming on the 17th of March! Learn more about the programme and see if you have what it takes to apply!

 

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