India’s up-and-coming AI/ML startups

India’s startup ecosystem is thriving, and one particular area of interest is that of artificial intelligence (AI) and machine learning (ML).

AI and analytics startups in India attracted US$762.5 million in funding in 2019, and India is currently the source of 8% of the world’s AI talent. Indeed, the country is in a position to be a major contributor of AI-driven solutions that address various issues not just in India but around the world.

We hear from three rising startups in India about how their technology could make a difference.

The following responses have been edited for brevity and clarity.

1. Intello Labs

The Intello Labs founding team / Photo credit: Intello Labs

Founded in 2016, Intello Labs uses AI/ML to automatically grade and analyze the quality of fresh produce, with the aim of increasing transparency in the supply chain as well as reduce value risk and food waste.

What is your core business or tech use case for which you use an AI or ML-based solution?

Intello Labs brings a new approach of evaluating fresh produce quality with the help of imaging technology and cutting-edge neural network AI.

Our clientele comprises large supermarket chains, ecommerce companies, growers, and aggregators for which we reduce value risk and increase revenues through customer satisfaction. We do this by providing real-time interventions, calls to action, and actionable insights for decision-makers through the use of AI/ML.

How has being on the cloud and Amazon Web Services helped your startup scale fast?

Our very first AI solutions for quality analysis of agri-commodities used mobile phones. They relied on cloud-based processing units, and they worked well – for a time.

After we took on multiple clients with global operations, we made the switch to AWS. Platforms such as AWS Lambda, Amazon SageMaker, and other AWS cloud services helped us iron out any wrinkles we faced quickly. They delivered on every promise.

What are your plans for the future?

We want to make our current products – Intello Track and Intello Sort – the de facto standard for agri-commodities quality assurance and wield them as smart, scalable solutions to reduce food wastage.

2. Vernacular.ai

Akshay Deshraj and Sourabh Gupta, founders of Vernacular.ai / Photo credit: Vernacular.ai

Vernacular.ai aims to make call center operations more efficient through the use of a voice AI platform in order to automate the process of providing customer service assistance.

What is your core business or tech use case for which you use an AI or ML-based solution?

We are an AI-first Software-as-a-Service business that automates enterprise contact centers through the Virtual Intelligent Voice Assistant (VIVA), a next-generation multilingual voice AI platform that understands customers’ queries and facilitates their resolution through natural human-like conversations.

This empowers companies to free up operational bandwidth so that they can provide faster and more efficient service. This change directly results in increased customer satisfaction scores and improved agent satisfaction. Our customers have seen a 40% reduction in average handle time and a 50% reduction in operational costs after implementing our solutions.

On top of that, we’re building a language understanding engine for the 7.5 billion global population. Our engine, which can understand the nuances of the languages spoken across demographics, is used by enterprises to build hyper-personalized experiences for their end users.

What inspired you to start an AI/ML startup?

Our founders Sourabh Gupta and Akshay Deshraj met in university through a campus group that was promoting entrepreneurship. They were already certain of what they wanted to do in life and ended up in Bangalore as entrepreneurs-in-residence at Kstart, a seed fund initiative by Kalaari Capital for Indian startups.

They decided to be more aggressive in their understanding of the public and spent two months traveling to villages and visiting rural areas, talking to farmers, small business owners, and people who fell under the category of lower middle-class households. In the end, one thing became clear to them: There was a huge underlying opportunity in the next 400 million Indians who were about to come online within the next five years, and that opportunity was language.

They subsequently realized that there was no interface yet that let users interact in their preferred language, and that businesses had a hard time engaging with their multilingual customers. They then went on to launch Vernacular.ai.

How has being on the cloud and AWS helped your startup scale fast?

We leverage AWS products for their on-cloud SaaS offerings and run our entire infrastructure on its Kubernetes cluster. We use the Amazon Elastic Kubernetes Service to orchestrate, deploy, and support more than 50 microservices in multiple production and staging environments. We also use AWS Auto Scaling to scale up workloads during peak hours.

We also leverage Amazon Elastic Compute Cloud to train our machine learning models, as well as Amazon’s Relational Databases and Amazon Simple Storage Service to store and analyze insights from the transactional and audio data that power our core product.

3. HyperVerge

The Hyperverge team / Photo credit: Hyperverge

Founded in 2013, HyperVerge develops AI models for the analysis of images and videos that help enterprise customers streamline their processes and work more effectively.

What is your core business or tech use case for which you use an AI or ML-based solution?

HyperVerge is a business-to-business software-as-a-service company providing AI-powered solutions in two areas. First, we provide solutions to enterprises in banking and financial services. Our fintech stack offers onboarding services, such as a digital and video know-your-customer (KYC) platform, fraud check, data verification, credit scoring, and contract verification.

We also offer a geospatial stack, which takes satellite or other map data, and identifies objects and detects changes. This is relevant to industries such as defense, energy, property tax, and insurance, which often need to make sense of a very high number of satellite images in a very short time. Our stack converts petabytes of data into actionable insights.

How has being on the cloud and Amazon Web Services helped your startup scale fast?

We had scaled to a point where we did 280 million KYCs in 2019. Being on cloud meant that we could use the elastic nature of cloud storage and auto-scaling options to scale without incurring the costs of an on-premise set up.

Cloud solutions have reached a stage where they provide systems that help a startup access the best in industry-standard development operation and security operation tools and systems, which help increase efficiency.

What are your plans for the future?

HyperVerge has grown 10x in revenue in 2019, and we are looking at hypergrowth in the years to come. Existing accounts are expanding in addition to new sales from products across multiple industries. All of these put together, the company is looking at a 4x growth year on year and is targeting to cross US$100 million in annual recurring revenue by 2023.

The team is also focused on building a long-lasting company and finding meaning by leveraging the team’s capabilities to bring positive changes into people’s lives. HyperVerge is currently identifying problem areas where we can focus our energies for maximum impact.

The APAC AI Conclave is a free virtual conference presented by Tech in Asia in partnership with Amazon Web Services, held on November 25 to 26, 2020. Missed the event? You can still hear from these companies and other experts in the AI/ML space about how startups and practitioners from the region can build smart, customer-centric, and scalable solutions in the cloud using the latest, broadest, and deepest set of machine learning and AI services.

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