Taken from Palava's Facebook page.
Palava Accelerator, a privately-developed greenfield smart city located in Mumbai Metropolitan Region, is now available as a test-bed for startup innovation, thanks to Lodha real estate group and Zone Startups.
“Palava Accelerator will aim at invigorating economic growth of Palava, bringing the first set of jobs within the city thereby making walk-to- work a reality for the citizens of Palava,” said Shaishav Dharia, Regional CEO of Lodha Group to ET.
Thirty startups will be enrolled into the program every year, provided with 4 months of acceleration. The process is implemented in partnership with Zone Startups, the accelerator operated by Toronto-based Ryerson Futures.
“Through the program, Palava would provide entrepreneurs an opportunity to work in the city and with the city management body, provide mentorship with reputed mentors in these fields, provide access to investors and a stimulating environment to work in,” reported Dharia.
The accelerator will be operating on eight to ten startups at a time, credits to funding provided by Lodha’s Startup Investment Fund for Real Estate and Smart Cities of Rs. 50 Crore ($11 million).
“We are hopeful that this initiative will encourage startups to create disruptive ideas, technologies for the real estate sector and take government’s smart city mission a notch higher,” stated Dharia.
Hopefully, among other initiatives, this will boost the startup movement in India, which the information technology minister of Karnataka, Priyank Kharge, said was “Full of slogans, but lacks actual news.”
Indian shoppers could be shopping internationally using their UPI accounts sitting at home, thanks to…
The SMS as a tool to connect with customers might be coming to an end.…
Looks like finance and connectivity will come together soon in our devices. Recently, UK fintech…
The Tech Panda takes a look at recent tech launches. Digital Infrastructure: End-to-end solution to…
In a major breakthrough against crime, India’s Narcotics Control Bureau (NCB), with support from the…
Abstract The article advocates for a more comprehensive evaluation method for Large Language Models (LLMs)…