How computer vision startup CamCom found success by pivoting from B2C to B2B

Bengaluru-based startup CamCom woke up to the enterprise market’s bigger opportunity, harnessing deep learning to automate quality checks and provide predictive and prescriptive solutions across a product’s life cycle.

Change is the only constant, and nowhere does this hold truer than in the dynamic world of technology. This realisation is what led two-year-old computer vision startup CamCom to pivot from a consumer market to enterprise customers.

The Bengaluru-based startup, founded by Ajith Nayar, Umesh and Mahesh Subramanian in 2017, began life with an image search technology that allowed people to discover new products. The founders decided to shift focus when they realised that it was not working because of “lack of accurate data and a wide market”.

Today, CamCom harnesses computer vision and deep learning to “automate quality checks across the product life cycle using mobile phones and other readily available cameras”. The startup has one aim: to be the preferred quality assurance partner for enterprises across the globe.

CamCom founders: (from left) Umesh, Mahesh Subramanian and Ajith Nayar

“We realised that our background was in enterprise technology and B2B was what we knew best. A random conversation with a customer made us realise the need to change,” says Ajith Nayar, Co-founder of CamCom.

Ajith previously worked with Wipro. The other co-founders also come with solid experience. Umesh used to work with Wipro and previously ran a startup while Mahesh is a serial entrepreneur-cum-angel investor in the area of deep tech.

Why did they pivot?

The customer who put bootstrapped CamCom on a divergent path was an online fashion apparel company facing the huge challenge of returns and unable to solve it. The company thought that the clothes were being returned because of wrong delivery from their warehouse.

However, after CamCom came into the picture and deployed its computer vision solution, the fashion firm realised that the problem was not with deliveries from the warehouse; it was because wrong items were coming into their system.

This led the startup to focus on the enterprise customer market, or what is commonly known as the business-to-business (B2B) segment. This has proved beneficial, leading to higher stickiness and greater stability in revenues.

Today, the startup has customers in the automotive, insurance, beverages, and apparel industries.

And despite the presence of numerous computer vision startups, CamCom believes its USP - how it deals with data – differentiates it from others.

Umesh says, “Most of them provide just basic interpretations of data, but we go beyond that. Our solutions are predictive and prescriptive.”

For example, during an engagement with an insurance company, the startup saw that they were getting a lot of claims regarding damage of rearview mirrors. On further analysis, CamCom found that the problem lay with a particular mirror manufacturer.

Providing actionable insights

CamCom is one of the few startups with expertise in both software and hardware. At present, its products include Automobile Defect and Damage Assessment, and Automated Quality Control.

Mahesh says, “Most companies say give us the data and we will give you analysis, but this does not translate into actionable insights.”

“We are not just a backend software provider; we also provide front-end automation like designing rigs with quality control on camera and lighting to capture the right images,” he adds.

According to the founders, another advantage of their technology is that their solution can be applied on existing platforms and there is no need to overhaul systems.

This pivot saw CamCom touch revenue of $3,50,000 in FY19. This bootstrapped startup, not profitable as yet, and has received an angel investment round of $200,000.

It follows a SaaS model for generating revenues; its technology platform can be operated remotely or reside at the location of the customer.

Focusing on select verticals

Given the wide applicability of its technology platform, this startup wants to narrow its focus on a few select verticals and go deeper.

“To spread ourselves is not going to help us; going deep into few select industries will help us in our accuracy,” Umesh says.

Mahesh concurs. “We need to move up and down the value chain of the industries we are focused on. We will keep ourselves ahead with investments in CamCom vision lab to stay ahead of the curve,” he says.

The three founders are extremely positive about future prospects. “The sheer breadth and applicability of computer vision technology has amazed us,” Ajith says.

At the same time, this startup does not believe in a growth trajectory at all costs. Umesh says, “We are fairly organised with highest adherence to all compliances, including legal.”

They continue to remain frugal in their operations, and are determined to make a deep impact with computer vision technologies.

The founders are at present focussed on the India market, but have plans to go overseas to geographies such as Southeast Asia and the Middle East.

(Edited by Teja Lele Desai)


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