Venture Catalysts backs smart helmet maker Altor

Venture Catalysts backs smart helmet maker Altor
Photo Credit: 123RF.com
10 Feb, 2020

Early-stage incubator and accelerator platform Venture Catalysts has invested an undisclosed amount in Altor, a Kolkata-based startup that makes internet of things (IoT) and artificial intelligence (AI) enabled helmets.

“We plan to use the current round of funding to optimise the product and to establish a clear market and client base, across several geographies,” Muhammad Bilal Shakil, co-founder and CTO of hardware at Altor, said in a statement.

Founded in 2018 by Shakil, Shamik Guha, Sayan Tapadar and Anirban Datta Gupta, Altor is operated by Praesus Technologies. This is the second round of funding at the company, the first being a 2018 investment from Ojas Medtech accelerator programme, an IIIT Hyderabad’s startup incubator, Guha told TechCircle.

The startup is currently operating on a pilot basis with multiple unnamed brands. By March 2021, the startup expects to roll out about 4,000 units, Guha added.

Altor says that its helmets are equipped with AI and IoT-enabled helmets, which will allow companies to track and monitor riders. The company claims to use a combination of hardware and software to offer in-vehicle data to companies that manage two-wheelers fleets.

Altor is Mumbai-based Venture Catalysts’ sixth investment in 2020, according to VCCEdge data.

Read: Venture Catalysts invests $70 mn in 63 deals this year

“While it is still growing, Altor has made great strides in this domain. Besides the hardware solution, its comprehensive SaaS model aids companies to increase fleet efficiency in a cost-effective way,” Apoorv Ranjan Sharma, president and co-founder at Venture Catalysts said.

The connected mobility solutions market is one of the fastest-growing ones in India and presents huge potential to investors, Sharma added.

Around 470 million connected vehicles are estimated to hit the roads by 2025, with a compound annual growth rate (CAGR) of 19% throughout the forecast period.

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