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Gigforce, the tech-driven staffing startup with a focus on gig workers, Tuesday said it raised $3 million in pre-Series A round led by Endiya Partners, with participation from existing investor Unitus Ventures and key angels.
The Gurugram-based startup will use the capital raised to strengthen its technology platforms, train gig workers, and scale to multiple cities.
Commenting on the fundraise, Chirag Mittal, Co-founder and CEO, Gigforce, said,
“The market is underserved today because of the lack of suitable technology to manage scale. India’s top five staffing companies together just about manage a workforce of one million. This is set to change with strong tailwinds, including the proliferation of inexpensive smartphones, ubiquitous Internet access for blue and grey collar workers, maturing technology platforms, simplification of labour codes, and the huge growth trajectory India will witness in the next 10 years.”
According to Gigforce, in the last 12 months, it has achieved an annual revenue run rate (ARR) of Rs 25 crore. It claims to grow 2X every quarter.
The startup said the huge demand surge in the recent months is expected to touch Rs 100 crore soon. Gigforce follows a vertical-specific strategy and focuses on the logistics sector. It already has over 20 enterprise clients categories, including ecommerce, food, and grocery deliveries.
It serves aggregators, marketplaces and direct-to-consumer brands, including Delhivery, Flipkart, BigBasket, FreshToHome, and Grab. Gigforce also focuses on specialised and fast-growing categories like electric vehicles, OEMs, and operators.
“Gigforce, well beyond the product-market fit, is clearly emerging as a category leader in tech-driven staffing for gig workers. With a potential to service up to 90 million jobs in India and contribute an incremental 1.25 percent to India’s GDP over eight to 10 years, there exists a huge opportunity waiting to be tapped,” said Abhishek Srivastava, Director, Endiya Partners.
Gigforce follows a deep data-based approach and tech-driven capability to optimally allocate skilled “gigers” to the right gigs.
