This startup combines e-commerce and offline shopping with 'camera commerce'

This startup combines e-commerce and offline shopping with 'camera commerce'

Monday February 19, 2018,

5 min Read

Through 'camcom' you can now do product discovery from offline and online merchants as well as do transactions. 

L to R: Sales head Ajith Nayar, CEO Umesh, CTO Pramod Solanky.

It was an article about the ridiculous number of food and beverage pictures on Instagram that started the conversation. For three techies based in Bengaluru, the idea was to enable product discovery with pictures taken from a mobile camera.

Fifty-four-year-old Andhra-ite from Chandigarh Uma Mahesh, who goes by Umesh, and his ex-colleague Ajith Nayar, 45, from Kerala were keen to startup. So was Ajith’s ex-colleague Pramod Solanky, 29, a Rajasthani from Chennai.

Their idea was simple: Offline shopping is the best way for product discovery, provides proximity and intimacy with a product, while ecommerce provides easier checkouts.

CamCommerce (Camera Commerce) can bridge this gap, and provides a unique way of product discovery (closest to the in-store experience) using a phone camera, assisted by computer vision Artificial Intelligence technology, and the ease of online checkouts.

CamCom app defaults to the phone camera. The consumer has to just click a picture of any product and CamCom analyses the image, classifies the product, and detects details about the product. It then uses NLP (Natural Language Processing) techniques to construct the product description. This description is shown to the consumer and the same is passed on to the merchant site to bring out options and prices for the consumer. The consumer can then select the product from options presented, and make a transaction.

Gifting experiences

The team, with their company Gifto, started off by trying to enable the gifting experience using a mobile phone camera. Their strategy was to sign up offline merchants in the category, and earn a commission on every transaction. The initial investment was around Rs 10 lakh.

The gifting use case was launched across seven outlets of Smoor Chocolates in Bengaluru in July-September 2017 as a pilot. It got them Rs 1 lakh in transaction revenue on app. (They trio had started operations at Mobile 10X incubator in February 2017.)

Umesh claims Gifto’s technology can be used by any large grocer to grade the quality of perishable items like vegetables. This technology can also be embedded in warehouse goods to grade and identify the quality of the lot, and Umesh claims it can even help identify rotten vegetables from good ones.

The same technology can be used by offline and online retailers to create product catalogues. “Today, this is very cumbersome and involves high level of human interaction. With this technology they can do it faster, more accurately and with far less workforce,” says Umesh.

Sustainable business model

Gifto enables visual discovery on multiple use-cases like mobile apps, and backend cataloging, enabling offline and online stores to integrate visual discovery on their platforms and apps, to pharmacy checkouts etc.

Umesh explains, “We provide two engagement models: platform as a service, and licensing and support model. A large US-based IT services provider in the travel space is using this technology to identify dog breeds so they can make the right choices for the kennels, food, and temperature requirements for pets to be transported from one place to another. Their consumer-facing app has our technology built into it for recognition.”

Gifto has already got two B2B paid assignments and has 12 more in the pipeline.

The B2C model is driven by Gifto’s App CamCom which enables instant recognition of transactable merchandise in the photo clicked. Gifto has partnered with Flipkart in India as the fulfillment partner.

“We are also in the process signing up other merchants. This will help us popularise visual discovery as a serious way to product discovery in future,” Umesh adds.

The company’s main target is women in the 18 to 34 age group. Umesh says, “Available data indicates that women are more trigger happy than men, and buy and gift on impulse more often than men.”

Many challenges

According to Umesh, not many are trained in this technology, and a lab-to-field dissemination is still being thought about. However, being based in Bengaluru has provided Gifto with the best available talent. Currently, the team has four engineers, one marketing resource, and three interns, besides the co-founders.

Since the technology for camera commerce is still in the nascence stage, research is on globally. Umesh adds most labs, from the US to Israel to Singapore to Japan, that are dabbling in visual AI are potential competition for Gifto.

“So are companies like Amazon, Facebook and Google who are also exploring the space seriously. At the end, the accuracy of recognition in the area of its application will see a clear winner. We feel we are on the right track on this one,” he adds.

Team Gifto is mentored by Ramprasad K, the creator of Holmes (Wipro AI Platform) in AI and Machine Learning, and data sciences expert Manohar Mulchandani for analytics.

Expansion plans

Gifto is working on Product-Category wise merchant affiliation model. In the future, Gifto could have Myntra for all fashion apparel and accessories, and Bigbasket for daily need items.

Gifto is targeting revenue of Rs 2 crore in FY2019, a bulk of it from B2B. Umesh says they will be profitable by FY 2020-21.

Gartner’s latest report says that by 2021, around 30 percent of commerce revenue will be influenced by visual and speech discovery. But for Gifto, the holy grail - unlike lots of tech companies - is not the US.

“We would like to be in South Korea and Japan because they are at least three years ahead of the rest of the world in tech and early adoption of anything new. Deep Learning is an evolving technology, we must continue to work hard to stay on top and keep experimenting,” Umesh says.

He adds their biggest success is being able to bring to market a monetisable version of a technology that is still very much lab-bound.

“We look up to companies and models like Facebook and Google who have changed the behavior of the consumers in the last 15 years. Hopefully, we can bring in that change using visual discovery,” he concludes.



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