Startups in India have observed tremendous growth despite all the challenges in the last few years. The greater digital adoption and investors’ increased tendency towards investing in early-age startups are major enablers for startup ecosystem growth in these years. Tech giant Amazon Web Services (AWS) has been empowering startups across industries to scale their business with the help of advanced digital technologies. Rajeev Ranjan, Editor, Digital Terminal recently interacted with Amitabh Nagpal, Head of Startup Ecosystem, Amazon Web Services India Private Limited (AWS India). He talked about the growth of startups in India, challenges and their efforts in helping them to grow. Read the complete interview below.
Rajeev: How do you see the evolution of the Indian startup segment?
Amitabh: India’s dynamic startup ecosystem is the third largest in the world, after the USA and China. The pandemic has marked a shift towards accelerated adoption of digital services, and startups have been at the forefront of this development. Using the power of cloud, startups across sectors are leveraging technology to innovate and build solutions to improve lives of millions of Indians.
The startup ecosystem in India has also matured, with greater focus on supporting founders with the resources they need to get started, based on increasingly nuanced needs. For instance, there’s a broad spectrum of unique resources such as “Micro VCs,” to global funds to verticalized funds (i.e. IOT, deep tech) to Angels and “Super Angels” that are available and accessible to founders at different stages of their entrepreneurial journey.
Furthermore, there is active promotion of entrepreneurship and startup-focused programs by the government departments and universities across India. This will continue to drive and support the rising wave of entrepreneurship and innovation in India. Today, there are more than 91,000 government recognised startups in India, and we can expect this number to increase as startups continue to build solutions to address unmet needs of people.
Rajeev: What remains the biggest challenge for the startup ecosystem in India?
Amitabh: Startups across sectors and at different stages of their journey face unique challenges. However, when we speak to our startup customers, we find that optimizing costs remains one of the major challenges for most startups. As a technology provider, we believe it’s important to enable cost optimization solutions for startups for whom every dollar counts, especially in the initial launch and growth phases of building a business.
After a period of rapid growth in the past few years, startups across all stages of growth are now focusing on cost optimization and being efficient in the use of resources. At AWS, we use many levers to help startups make optimal use of cloud and reduce costs, without compromising on productivity or scalability. For instance, our customer Atlan launched their multi-tenant SaaS platform on AWS Cloud using Amazon EC2 Spot Instances in conjunction with Amazon EKS for stateless applications. Atlan was able to scale their deployment seamlessly across 100+ customers globally leveraging AWS Global Infrastructure, and at the same time managed to reduce its computing costs by 50–70% leveraging Amazon EKS on spot instances, as compared to On-Demand instances.
The cost-effective nature of the cloud means startups can experiment at a greater pace, fail fast with low financial impact, and recover easily. At AWS, we focus on reducing a startup customer’s cloud bill. Since our inception, AWS has reduced prices 129 times.
Rajeev: What is the role of AWS in boosting the growth of startups across all verticals?
Amitabh: Startups across the country are using AWS technologies to innovate, experiment, grow and scale. With over 200 products and services, we have the broadest and deepest set of capabilities of any cloud provider, ranging from basic computing and storage to advanced database and architecture options, to pre-built solutions. We work startup across sectors to help them leverage cloud for their growth and success.
For example, SaaS startup Amnic uses AWS’s managed services like Amazon Elastic Kubernetes Service (EKS) to enable startups to take advantage of all the performance, scale, reliability, and availability of AWS infrastructure. With AWS as their technology backbone, Amnic’s solutions enable startups to focus on building their product and growing business, without investing in and deploying resources to build and scale their infrastructure stack on the cloud. This has helped Amnic’s customers to enhance developer productivity by up to 25% and reduce costs by up to 20%.
In the fintech space, RING aims to provide digital financial services to underserved millennials through its transactional credit app. AWS machine learning services help RING make quick credit decisions, underwriting, fraud detection, and document processing. Using AWS services, RING reduced its non-performing assets (NPA’s) by 20%-25% and delivered a customer retention rate of over 90% for the past 16-18 months. The startup has also successfully reduced the customer wait time by 50%, collection delinquency by 25%, and cost of collection by 30%, by using AWS to power smart analytics and drive high efficiency through the appropriate allocation of resources.
Another fintech customer, INDmoney, a “super money app” that offers users a complete solution to track, save, and grow their financial assets, reduced its computing costs with Amazon ECS on-spot instances. The startup also uses AWS to automate scaling for massive growth, improving resiliency with isolated containers, and analysing data to provide customized recommendations to its users.
Agritech and healthtech are two verticals where we are seeing interesting innovations. DeHaat is an agritech platform with a mission to solve the challenges faced by farmers, and it needed a cloud platform that is flexible and mature to target the massive scale of farmers. DeHaat moved to Amazon SageMaker, which enabled them to seamlessly create, train, and deploy machine-learning models in the cloud. By utilizing AWS services, DeHaat was able to provide cost savings of upto 15% to farmers. With the crop mapping AI model in place, DeHaat is currently at 90%+ accuracy in predicting the acreage and was able to save on the operational cost.
Healthtech startup, HealthifyMe's latest offering is HealthifyPro, which is its most advanced personalized metabolic health program. With HealthifyPro, the company is also pioneering a "virtual Continuous Glucose Monitor" to predict glucose values without having a physical device by using Amazon SageMaker to build the machine learning (ML) models for prediction. Amazon Sagemaker helps build, train, and deploy ML models for any use case with fully managed infrastructure, tools, and workflows. HealthifyPro also uses AWS services like Amazon OpenSearch, Amazon Elastic Container Service (ECS) & Amazon RDS to deliver superior health outcomes.
Similarly, in gaming, Games24x7, India's leading gaming company with a portfolio that spans skill games and casual games ramped up its utilization of Amazon SageMaker to personalize the user experience with ML and scale user base by 400% in 2 years.
Rajeev: Tell us about the ML Elevate programme and how does it empower startups using AI/ML?
Amitabh: At AWS, we help startups build a strong technology foundation, and also support them to grow and scale their business through programs such as ML Elevate, which is an intensive 6-week programme designed to nurture and empower early-stage machine learning (AI-first or ML-core) startups.
The challenges faced by a ML founder are unique, as they start on the journey of setting up a strong technical foundation, streamlining ML Ops, iteratively evolve their product to achieve market fit, winning initial customers, hiring the leadership team, and going global. ML Elevate is designed to help solve these challenges and nurture, empower and accelerate ML startups, by working backwords from the needs of a ML startup founder.
Last year, we ran the ML Elevate program, in association with Accel and Intel, through which the selected startups got access to mentorship from industry leaders, community of leading AI/ML startup founders, curated resources, AWS Activate credits, knowledge sessions by subject matter experts on product-market fit, scaling product, building go-to-market strategy, team building, and many other topics. The program also provided startup teams access to AWS experts for best practices and guidance to help organizations get the most out of their machine-learning initiatives. The program concluded with a demo day, which offered the selected startups an opportunity to pitch to top-tier investors.
Rajeev: What according to you are the trends for AI/ML in 2023?
Amitabh: ML and AI technologies have the potential to impact almost every business and transform how they operate. Over 100,000 global customers across industries rely on AWS for ML and AI initiatives that infuse AI into a broad range of business use cases to automate tasks, drive greater efficiencies and lower operational costs. One example of how startups are using AWS to power their AI-led solutions is Blend, a deep-learning-powered photo and design editing app that democratizes access to studio-quality photography and generative AI. SMB sellers use Blend around the world to create professional product visuals in just 3 clicks to stand out, and sell more online.
Blend identifies the product and its pose in the photo, instantly removes the background, and automatically generates thousands of designs optimized for 16 e-commerce marketplaces and 8 social media platforms within minutes. The startup built on AWS from Day 1, and uses services like Amazon SageMaker to deploy and scale its machine-learning models. Blend’s deep learning algorithms generate more than a million designs every day, supporting thousands of e-commerce businesses to create ready-to-use product listings and marketing images.
As companies look for solutions to enable automation and bring in more efficiencies, there will be more adoption of AI/ML technologies. For instance, one of tech predictions by Werner Vogels, CTO at Amazon, is that adoption of technologies, such as computer vision and deep learning, will transform supply chain. With proliferation of IoT sensors in factories, machine learning will be used to not only predict machine failures, but also prevent them. This will lead to less downtime and drive more consistent production.
Harnessing data to train ML models will also see enhancements to make the process more flexible and streamlined. At AWS re:Invent 2022, AWS announced latest innovations that will make it easier for organizations to use machine learning technology, including purpose-built solutions to solve industry-specific challenges. The announcements unveiled new capabilities for Amazon SageMaker, AWS’s end-to-end ML service, as well as new database and analytics capabilities that will make it easier for customers to query, manage, and scale their data.
Rajeev: How do you plan to associate with more customers? Do you have a channel partner network to sell the latest solutions to emerging players?
Amitabh: We work with hundreds of thousands of customers globally, and are supported by a robust partner ecosystem. AWS approaches how we partner differently. We lead with the customer first and design our strategies to enable AWS Partners to deliver high-quality AWS solutions and services to joint customers. AWS provides partners with innovative programs and services to build and grow their businesses. We also work with investors, incubators, accelerators and other stakeholders in the ecosystem, through various programmatic approaches.
We leverage this network to facilitate connections and help our customers drive benefits. For instance, we worked with cloud-based marketing automation startup MoEngage to support their expansion from India and into the ASEAN region by connecting them with more than 230 Chief Marketing Officers of enterprise clients from six countries, resulting in seven new deals.
