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Startups Artificial Intelligence Marketing

How Squad plans to expand globally by coalescing artificial intelligence and human intelligence

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By Taruka Srivastav, Reporter

April 19, 2017 | 6 min read

AI SaaS startup Squad recently raised $2.1m for its AI technology and it is now planning growth at home and globally.

Squad team

Squad - Apurv Agrawal (back row, second from left), Vikas Gulati (back row, centre) and Kanika Jain (back row, first from right)

The investment came from India and Valley-based investors like Blume Ventures, Contrarian Capital, 91springboard, Emergent Ventures, Abstract Ventures, Anthill Ventures, Axilor Ventures, as well as from angel investors, Gokul Rajaram, product engineering lead at Square, and Shamik Sharma, senior technology advisor at Myntra.

Squad will use the funds to gauge its platform by expanding the technology, product and data teams in India and the sales team in the US.

Squad automates business processes for enterprises by combining human intelligence and artificial intelligence, helping businesses scale with unprecedented speed, accuracy, flexibility, and cost reductions. Leaders in digital commerce like Uber, Sephora, Tata Group, Flipkart Group, Rocket Internet Group, Teespring and other data-intensive businesses use the Squad platform across their entire data cycle.

Squad founder Apurv Agrawal outlines what this investment will mean globally and how its take on AI has already won the business from many household names.

Tell us a little about your startup and how you came up with that idea

We are solving the problem of unstructured data and how it's processed to derive value. The Problem is that very business in the world, regardless of location, industry and size, has massive amounts of unstructured data that needs to be processed for operations, product, and profitability.

Companies usually deploy engineers to build out admin panels and ‘throw’ a large workforce to scale operations. This gets you great quality and control but comes at a steep price and is hard to scale. The next innovation in this process was in late 90’s and meant offshoring the workforce. This reduced both the quality and the cost but the trade-off was OK for a lot of companies. The fixed costs and inflexibility still remained. Outsourcing created a wave of ‘service’ led businesses and industries in developing nations. We then saw crowdsourcing emerge, with a lot of promise, but it failed to create a massive impact for several reasons, including quality and reliability. We now see AI as the new frontier, which holds a lot of promise, though it is probably hyped up, and remains largely untested for a lot of applications.

With over 88% of transactional (user) data still being unstructured and expected to grow by 10x over the next 5 years, scaling operations continues to be an ongoing challenge.

The promise of Artificial Intelligence (AI) through machine learning has everyone hooked! Many have committed significant resources to train algorithms on large datasets, trying to push boundaries on what’s achievable. However, one of the biggest misconceptions about artificial intelligence is the belief that today’s AIs possess generalised intelligence. What we are really good at right now is leveraging large data sets to accomplish specific tasks that are plain, bounded, repetitive and systematic in nature. We fall flat at replicating the breadth of human intelligence.

As AI has become increasingly familiar and mainstream, what has garnered less attention and resources is human intelligence (HI). With advances in information technology, cheaper processing costs, robotics, and artificial intelligence developing at a rapid rate, workforce dislocations are predicted to accelerate in the coming years. We seem to be saddled with a bullet to bite - automation (AI) helps innovation flourish and brings cost savings for businesses, but also displaces jobs (HI).

HI is unique, because of its unparalleled ability to design, modify and build new forms of intelligence. HI is what defines us as humans and our relationship with everything around us. Now, through the combination of HI and AI, we are at the brink of intelligence enhancement, which could be the most consequential technological development of our time, and in history.

Individually, HI and AI might have their limitations today. Making them work together can help us extract the best value from both. At Squad, we have recognised this. So we developed a smart workflow builder that gives enterprises access to high quality automation (AI) and a highly curated and quality distributed workforce (HI) in a single platform.

Tell us about the latest fundraising of $2.1m

Over the years we have achieved the product market fit and felt that it was the right time to aggressively invest in scaling the platform in terms of technology and capability. We want to expand into more traditional industries and, for that purpose, raising funds and having strategic investors was an important step.

What are your further global expansion plans?

From a growth standpoint, we want to make a move to the more traditional industries like banking, telecom, insurance etc. We are reimagining how work gets done and want to provide tools to operations teams across the globe to help automate their work.

Your startup is in San Francisco as well as India. How has the response been so far? Tell us about your work there

The response in the Bay has been pretty good so far. Everyone we meet is saying that this could be big and that gives us a lot of confidence to do what we do. We are known in the industry now but there's still a lot that needs to be done. We are now in the process of scaling our US team.

With your focus on tech and AI, wallet payments are becoming the way of life in Indian economy, what is your comment on this?

It's a great move that we are headed in the direction of a cashless economy. I am for it.

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