California-based AgShift, a deep-learning tech startup, is building an autonomous food inspection system to reduce global waste. The company claims its the first system of its kind. Last week, AgShift announced that it had raised a seed amount – US$2 million – from early-stage fund Exfinity Ventures which is focused on frontier technologies shaping the future. Their focus is primarily on enterprise companies (B2B) in India and across the India-USA business corridor.
The work that AgShift is doing caught the attention of the investors and Managing Partner and CIO of Exfinity Ventures, Shailesh Ghorpade, shared, “The AgShift team is truly leading the transition of food inspection and quality assessment into the data-driven era. AgShift’s unique application of deep learning with a challenging proposition truly excites us.”
Miku Jha is the Founder and CEO of this Silicon Valley-based company which was started in 2016. The company is re-imagining food inspection at multi-levels and hoping to standardise it across the entire supply chain to reduce inconsistencies in food quality, and thereby reduce food wastage. In a statement released by the company, Miku shares, “Current food inspection processes are paper-based and tedious, needing continuous personal training. Inconsistent and subjective inspections result in a loss of $15.6 billion a year for the organizations responsible – not counting the millions of dollars in recovery costs, claim management, and loss of brand reputation incurred by the companies involved.”
According to Miku, AgShift can make a huge impact on reducing 1.3 billion tons of annual food loss and waste.
How does AgShift do it? Deep Learning (hierarchical learning) is machine learning based on data representations, as opposed to task-specific algorithms. At AgShift, it is clubbed with Computer Vision, an interdisciplinary field that works on making computers gain high-level understanding from digital images or videos. Using computer vision and deep learning to autonomously inspect produce and other commodities for defects, AgShift facilitates quality assessments and better judgements as per USDA specifications or organizations’ own specifications. According to the company, their patented deep learning models analyze the defects in the sample images and predict the overall quality of the sample.
“The platform relies on curated, extensive real-world image data sets to teach our software to analyze defects with high consistency and accuracy – every time. The solution augments manual inspections – providing objective, consistent, and standardized quality interpretation across the supply chain – every single time,” the company shares.
This is not Miku’s first venture. She is a seasoned entrepreneur who has led multiple startups and led a few to mergers and acquisitions with companies like IBM and Xyratex. She holds a Bachelor’s degree in Computer Science from the University of Mumbai and holds an MBA from Cornell University. Miku also serves on the advisory board of BetterMDM (a cloud-based software enterprise company), PlainMark (a mobile apps risk assessment platform), and MergeLane (a Boulder-based investment fund and accelerator that invests in companies with female leadership).
AgShift’s team comprises of around 20 members who have extensive experience across food and technology industries, with professional tenures at VMware, Intel, IBM, and Topco. The seed investment is also a testament to the work the team at AgShift is doing, and the capital will be used to develop the team and the product.
Miku says on the subject, “We have proven out our core technology working with these great partners. Now, with new capital, we will work towards strengthening our development team and maturing the product for specific enterprise and use cases as we continue to establish AgShift as a standard and platform of choice for autonomous food inspection.”