Exfinity Ventures leads seed funding in US-based AgShift

By Shweta Sharma

  • 23 Mar 2018
Exfinity Ventures leads seed funding in US-based AgShift
Credit: Shah Junaid/VCCircle

AgShift Inc., a California-based startup which is building an autonomous food inspection system using deep learning, has raised $2 million (Rs 13 crore) in seed funding.

The funding round was led by early-stage investor Exfinity Venture Partners, the startup said in a statement.

The startup will use the money to strengthen product development and expand customer reach. AgShift is working with a few food companies to bring its product to market.


“Current food inspection processes are paper-based and tedious, needing continuous personal training,” said Miku Jha, founder and chief executive, AgShift.

“At AgShift, we are re-imagining food inspection at various layers – starting from digitising product specifications, using a mobile-first approach for operational efficiencies to leveraging deep learning to make inspections autonomous,” she said.

Jha said the startup's goal is to standardise food inspection across the entire supply chain and reduce food wastage resulting from inconsistencies in food quality interpretation.


Jha, a former IBM and VMware executive, founded AgShift in 2016. At IBM, she led several mobile and Internet of Things initiatives under Mobile First portfolio. At VMware she was part of the mobile virtualisation team. Besides these stints, she has also built and scaled multiple storage and mobile software startups. She was part of the engineering team at ARIO Data Networks, a storage solutions firm, which was acquired by Xyratex, a data storage technology company, in 2006. She also worked at Worklight, an Israeli-based provider of mobile software for smartphones and tablets. The firm was acquired by IBM in 2012.

At AgShift, Jha is joined by Dr Amit Bhaduri, who heads technology at the startup, and Rob O’Rourke, who is head of business.

AgShift is building an autonomous food inspection system using deep learning to strengthen product development and expand customer reach. Its software blends patented deep learning models with computer vision to make food inspections autonomous, consistent and standardised at scale.


Investment banking firm JR Laddha Financial Services Pvt. Ltd advised on this transaction through its Singapore arm Coinage Consultant Pte Ltd.

Exfinity Venture Partners

Exfinity is a technology-focussed VC firm. It invests in technology-led product startups through Exfinity Technology Fund – Series I, which has a corpus of Rs 125 crore. The firm is led by IT industry bigwigs V Balakrishnan, Mohandas Pai, Deepak Ghaisas and Girish Paranjpe.


In October 2017, it invested $2 million (Rs 13 crore) in GridRaster Inc., which provides virtual reality (VR) and augmented reality (AR) experiences on mobile devices.

In April 2017, it led a $1.23-million pre-Series A round in Bangalore-based artificial intelligence and VR technology startup Absentia Virtual Reality Pvt. Ltd.

Some of its other investments include B2B marketing automation firm MarianaIQ, online fitness discovery platform Fitternity, Chennai-based computer vision and artificial intelligence company, Mad Street Den, and logistics management platform Locus.


Deals in the agri-tech space

Last week, agri-tech startups Sabziwala and LivLush, which are both backed by impact VC fund Elevar Equity, merged their businesses under a new entity named Kamatan.

Earlier this month, Indore-based Agstack Technologies Pvt. Ltd, which owns and operates agri-tech startup Gramophone.in, raised Rs 6.4 crore (about $1 million) from Info Edge (India) Ltd.

Around the same time, Bengaluru-based 63Ideas Infolabs Pvt Ltd, which runs business-to-business agri-marketing platform Ninjacart, raised about $1.1 million (Rs 7 crore) from venture debt firm Trifecta Capital.

Last month, Agricxlab, an agri-tech venture that uses smartphone imaging to assess the quality of agri produce, raised a seed round worth $500,000 (Rs 3.2 crore) led by early-stage venture capital firm Ankur Capital.

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