funding 2021-10-08

Ishitva Raises Over $1 Mn Pre-Series A Led By Inflection Point Ventures

Funds raised to be used for growing sales and expanding the R&D team

By Content Writer
Ishitva Raises Over $1 Mn Pre-Series A Led By Inflection Point Ventures

Ahmedabad-based robotic startup, Ishitva on Friday announced to have raised a pre-Series A round of over $1 million led by angel investment platform Inflection Point Ventures (IPV).

Many waste management and plastic value chain players and veterans also participated including Kamaljyot Investments Ltd (a subsidiary of Excel Industries Ltd), Gandhi Family from GRP Ltd., AVI Global Plast Private Limited, Anup Gulati of Quality Maritime Provider Lda., Harinder Arya of Major Capex & Joulon, Sanjay Kamlani of Pangea3 and Mohan Ayyangar of GDS EY India.

The funds raised will be utilized in growing sales and expanding the R&D team.

“Indian waste management industry is a riddle and our unlimited dream is to eliminate the manual sorting of waste which often involves humans to work unhygienic conditions. Our vision is to install industry 4.0 solutions in more than 4000 towns of the country picked up by Swachh Bharat mission and we are thrilled to have IPV as a part of this journey,” said Jitesh Dadlani, founder, Ishitva.

Ishitva uses AI, ML, IoT Industry 4.0 to build efficient solutions which help in sorting complex waste. Effective sorting of waste is currently the weakest link in creating a circular value chain. Therefore, to avoid dumping and burning of dry waste, which leads to serious environmental hazards, the company focuses on leveraging industry 4.0 tools to systematically sort out waste and assess the quality of recyclable waste.

“We are excited that many of the waste industry stalwarts are joining early in our journey. With IPV, we now have access to a large pool of professionals and experts which is immensely useful at this stage for us,” shared Sandip Singh, chief executive officer, Ishitva.

Ishitva currently offers a range of solutions including SUKA (AI-powered air sorting), YUTA, (AI-powered robotic sorting), and Netra AI Vision system which helps in identifying waste and smart bins. The AI-powered Netra identifies the waste, learns about its contents by capturing images, and then scans for recyclable material.

 “According to MoHUA, as of January 2020, India generated 1,47,613 MT of solid waste. This is a serious situation that our country is headed to and we are seeing startups taking on this challenge to address the waste generated in the country. Ishitva’s model is particularly innovative as they are leveraging cutting-edge technology to sort out the waste which is already being generated. Sorting the waste is the first step to a meaningful recycling ecosystem. Ishitva’s business vision and our ESG goals are a seamless synergy which prompted us to invest in the company,” added Mitesh Shah, co-founder, IPV.

Waste sorting in India is currently mostly done by humans. The process is not only unhygienic and tedious but also dangerous for human beings. Using the powerful ishitvAI algorithm, the startup has built one of the most advanced Air Sorting Solutions SUKA 1.3, with the capability to sort up to 6 tons of plastic waste/ hour.  This system is an answer to various sorting challenges faced by the industry including Black Plastic, Multilayer packaging (including MLP flexibles), Objects with sleeves, Objects with dirt layer on top, Brand identification, and quantification, etc. In addition, their next industry-changing concept is a fully automated material recovery facility which provides the last level of segregation without any human intervention, the platform said. 

Only 10 per cent of waste is recycled in the World and the balance goes for dumping in land, water bodies, oceans, and incineration. About 66 per cent of global waste is generated in low-income countries, therefore, we need solutions that can be adopted by these economies to solve this global problem. With the use of Artificial Intelligence and Machine Vision, Ishitva has been able to make material recovery efficient for low-income countries, even for the decentralized and smaller size operations, it further shared. 
 
 
 
 
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