What does it take to qualify as an AI startup? At what stage do they need financial support? And lastly, what should the ideal mode of financing be? These critical topics came up for discussion when government officials recently met with key industry figures.

The focus of the meeting was AI startups in the context of the IndiaAI Mission. 

Notable attendees of the meeting included Google, NVIDIA, and Microsoft, and representatives from AI startups such as Jivi and DronaMaps were also present, the Hindustan Times said.

It’s encouraging to see the government recognise the rapid growth of AI startups across India and acknowledge the significant role they could play in driving the country’s economy in the coming years.

On a recent podcast, Rahul Agarwalla, managing partner at SenseAI Ventures, said he witnessed about 500 new AI startups emerge in the past six months, which is a massive number.

Based on the rate at which AI startups are popping up in the country, Agarwalla believes India could soon have 100 AI unicorns. While it remains to be seen when that happens, the budding AI ecosystem in India will indeed need support from the government beyond regulatory favours.

What Qualifies as an AI Startup?

A key topic discussed at the meeting was the criteria to define an AI startup. 

Attendees highlighted to the government that simply having ‘AI’ in their name does not automatically make a startup an AI-focused company.

In response, stakeholders proposed a rating system, which builds credibility among startups and would in turn make them eligible for government funding. Not everyone will make the cut though. 

Unfortunately, in the startup world, a majority of them do not live long enough to see the light at the end of the tunnel. 

Stakeholders recommend that rather than spreading a small amount of funding thin across many startups, the government should focus on identifying those with significant potential and provide them with targeted financial support.

Earlier, the government had allocated INR 10,372 crore as part of the India AI Mission – a part of which will be used to fund startups.

Should the Government Play the VC?

According to a Tracxn report, Indian AI startups raised $8.2 million in the April-June quarter, while their US counterparts raised $27 billion during the same period.

While not many Indian startups are building LLMs, which cost billions of dollars, the funding for AI startups in India still remains relatively low.

The government, under the IndiaAI Mission, is weighing options to fund AI startups and deciding how best to do so. One bold proposal on the table was taking equity stakes in these emerging companies.

The government had previously suggested taking the equity route as part of the second phase of the designed-linked incentive (DLI) scheme for semiconductor companies. However, the thought was not well received by many in the industry. 

“[I] don’t understand the logic of the government trying to become a venture capital firm for chip design companies. This move is likely to be ineffective and inefficient,” Pranay Kotasthane, a public policy researcher, said back then.

They fear government taking equity could lead to government influence over company operations, and historically, public sector companies in India have often underperformed. Moreover, it could push other venture capitalists away.

Access to Datasets and Compute 

Stakeholders were also quick to point out that more than financing, what the startups need is help in terms of compute. 

According to Abhishek Singh, additional secretary, ministry of electronics and information technology (MeitY), the government plans to disburse INR 5,000 crore of the allocated INR 10,372 crore to procure GPUs.

The government was quick to identify the need for compute, especially for Indian startups, researchers, and other institutions. In fact, last year, the government revealed its intention to build a 25,000 GPU cluster for Indian startups. 

Interestingly, PM Narendra Modi also met Jensen Huang, the CEO of NVIDIA, the company producing the most sought-after GPUs in the market, during his visit to India in 2023.

(Source: NVIDIA)

The Indian Express reported earlier this month that the government had finalised a tender to acquire 1,000 GPUs as part of the IndiaAI Mission. These GPUs will provide computing capacity to Indian startups, researchers, public sector agencies, and other government-approved entities.

Besides access to compute, the stakeholders also urged the government to make the datasets under the IndiaAI Mission available as soon as possible. The datasets will grant startups access to non-personal domain-specific data from government ministries to train models.

Notably, the Bhashini initiative is playing a crucial role in democratising access to Indic language datasets and tools for the Indian ecosystem.

India Startup 2.0 

While the government’s recognition of the funding gap in AI startups and its willingness to provide financial support is encouraging, it is equally important that the government creates a favourable environment for these businesses to thrive.

In line with this, the government launched the Startup India programme in 2016 to foster a robust ecosystem for innovation and entrepreneurship in the country. 

This initiative was designed to drive economic growth and create large-scale employment opportunities by supporting startups through various means. Perhaps, the need of the hour is a similar programme designed specifically for AI startups.

As part of the startup programme, the government identified 92,000 startups and, in addition to funding, provided support such as income tax exemption for three years, credit guarantee schemes, ease of procurement, support for intellectual property protection, and international market access.

Moreover, over 50 regulatory reforms were undertaken by the government since 2016 to enhance the ease of doing business, ease of raising capital, and reduce the compliance burden for the startup ecosystem.

Now, a similar ecosystem needs to emerge for AI startups as well, which fosters innovation, provides essential resources, and facilitates collaboration among researchers, developers, and investors to drive growth and success in the field.

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India-based startup Revrag has announced that it has secured $600K in its pre-seed funding round. The startup is building AI agents designed for revenue teams, and its first product, an AI-BDR (Business Development Representative), is set to launch soon.

The AI agent will automate prospecting and outreach at scale, intelligently qualify leads, schedule meetings, and provide data-driven insights for more informed decision-making.

Their first AI agent, Emma, is a fundamental shift in how the sales industry will evolve with modern technology, according to the startup.

While Revrag plans to explore many other territories, they are currently focusing on critical business operations like sales and marketing.

The pre-seed round of funding was led by Powerhouse Ventures, with participation from notable investors including Viral Bajaria (co-founder of 6Sense), Kunal Shah (founder of Cred), Deepak Anchala (founder of Slintel), Vetri Vellore (founder of Rhythms), and 20 other marquee angel investors.

Revrag is also backed by industry powerhouses, including founders and senior executives of 6Sense and Slintel.

“At Revrag, we’re building intelligent AI agents to help revenue teams automate their redundant work so they can focus on what’s important. For example, our AI-BDR can smoothly take care of the initial prospect outreach and schedule meetings, allowing human sellers to focus more on client interactions and other complexities of the sales process,” Ashutosh Singh, CEO and co-founder at Revrag, said.

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A lot goes into making the videos we consume online—brainstorming ideas, writing scripts, editing, and recording voice-overs—and all of this consumes a substantial amount of the content creators’ time. 

This is where generative AI can step in to ease the burden. It can be a great tool for the creators to streamline these processes and reduce the time spent on routine tasks.

Imagine an AI tool that lets you accomplish everything at one place with just a few prompts. InVideo AI promises exactly that, which is why content creators around the globe are falling in love with the platform.

According to Sanket Shah, co-founder and CEO of InVideo, the platform gets nearly 3 million new users every month. 

“We don’t track the total number of people using our free product, but if we take 3 million on average, we could have around 35 million users on our platform in just one year. In terms of paid users, we have about 150,000 of them,” he said.

AIM met Shah in early August in the Bengaluru edition of AWS GenAI Loft, a collaborative gathering of developers, startups, and AI enthusiasts to learn, build, and connect.

Shah revealed that the startup has already secured over 50% of its $30 million revenue target for the year.

Avoiding the Uncanny Valley

Interestingly, InVideo has not developed a text-to-video model like OpenAI’s Sora or Kling. Instead, the startup has partnered with several media providers like Getty Images and Shutterstock and pays them a licence fee. 

One primary reason for this approach, according to Shah, is that InVideo wants to provide users with publishable videos. 

Currently, even though models like Sora produce high-quality videos, there is limited clarity about the datasets they are trained on, which complicates the publishability of these videos.

“Moreover, at InVideo, one of our core principles is to avoid anything that falls into the uncanny valley. As of last week, we felt that generative image and video technology still often produced results with issues like extra fingers or multiple eyes—things that are not acceptable for our purposes. 

“We focus on delivering high-quality, publishable videos, so we prioritise ensuring that our users receive content that meets professional standards,” Shah said. 

The platform leverages AI to understand the user’s intent, write script, handle voice-overs—practically cloning the user’s voice. 

It selects and integrates media, performs editing tasks, adds music, and ensures that all elements like transitions and zooms are correctly applied, effectively automating much of the post-production process.

However, the startup does not shy away from leveraging models like Sora. Once available, they could contemplate integrating Sora and Kling into their platform. However, they are not in the business of building models.

“We don’t want to enter into a race with the hyperscalers (model builders) to build the next-big model. Models are also perishable and we have seen that already,” he said.

The AI in InVideo 

While the startup is refraining from entering the territory of model builders like OpenAI, Anthropic, Microsoft, and Google, it is building models that suit its business model.

“We prefer to focus on developing models that are niche and highly specific to our needs. For instance, we are working on a lip-sync model tailored to our requirements,” Shah revealed.

The startup also plans a new AI-powered feature next month, which allows users to create an avatar or a digital clone of themselves. 

“Here’s how it works– you record a short video, speaking for 30 seconds to a minute, and the AI generates an avatar. Once you have your avatar, you can input a prompt or specify what you want it to say,” Shah revealed.

The platform does leverage LLMs from Anthropic, OpenAI and Google, but Shah refrained from revealing much about their use cases. “This is very proprietary and that is where most of the magic happens.”

InVideo also leverages Amazon Bedrock, which gives them access to some of the top LLMs through a single API. 

Moreover, the startup also leverages AWS’ multi-region fleet of Spot GPUs for video rendering and editing on open-source solutions, allowing them to run 90% of their workload on Spot instances, which enables close to 40% cost reduction.

Enabling Content Creators with AI

The startup started with a pre-AI product in 2017 and was initially focussed on enterprises. However, pivoting to AI and to a more B2C business model from B2B proved to be a game changer.

Today, it caters to YouTubers and established and new content creators creating content for Facebook, Instagram, and TikTok. 

“The platform is also leveraged by small businesses, for example, a lady selling horses in Texas, a partially deaf teacher in Palo Alto who is teaching a community college, a bunch of students and teachers, someone selling water bottles, and some restaurants,” Shah revealed. 

“About 5% of our customers are also filmmakers.”

When AIM asked Shah about some of the most fun and interesting videos he has seen users generate using the platform, he revealed that the brand manager of the legendary rock band Aerosmith used InVideo to generate content on how to deal with depression.

“One day, the brand manager received an email from a viewer who was contemplating suicide. After watching the video and following some advice, they decided against it. Stories like these are incredibly powerful,” Shah revealed.

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Salcit Technologies, an Indian respiratory healthcare startup, is pioneering the use of Google’s Health Acoustic Representations (HeAR) bioacoustic foundation model to revolutionise tuberculosis (TB) detection in India. 

The startup aims to enhance early TB detection through the analysis of cough sounds, leveraging the HeAR model’s vast training on approximately 300 million audio samples, including 100 million cough sounds. 

AI TB Screening

Salcit Technologies plans to integrate the HeAR model with its existing product, Swaasa, which has a track record of employing machine learning for early disease detection. Swaasa has been instrumental in offering location-independent, equipment-free respiratory health assessments, bridging significant gaps in healthcare delivery across India. 

By harnessing HeAR’s capabilities, Salcit intends to make TB screening more widespread and accessible, especially in areas with limited access to advanced medical resources.

HeAR, which was publicly introduced in March 2024, is designed to assist researchers in building models capable of listening to human sounds and identifying early signs of disease. 

Sujay Kakarmath, a product manager at Google Research, emphasised the model’s accessibility, stating, “Compared to blood tests and imaging, sound is by far the most accessible piece of information that we can get about a person. HeAR can pick up chest x-ray findings, tuberculosis and even detect COVID from cough sounds.”

HeAR’s Potential in Global Health

Shravya Shetty, Director and Engineering Lead at Google Research, highlighted HeAR’s ability to discern patterns within health-related sounds, making it a powerful tool for medical audio analysis. Shetty noted, “We found that, on average, HeAR ranks higher than other models on a wide range of tasks and for generalising across microphones, demonstrating its superior ability to capture meaningful patterns in health-related acoustic data.”

“In places where access to Advanced Medical resources is scarce, we can imagine a future where a healthcare professional with a machine learning model and a phone can collect a sample of your sound and inform clinical care,” said Kakarmath. 

The Stop TB Partnership, a United Nations-hosted organisation committed to ending TB by 2030, also supports this innovative approach. 

Google’s invitation for researchers to explore HeAR’s potential through its API signifies a major advancement in acoustic health research. Salcit Technologies’ application of HeAR in TB detection underscores the model’s promise in addressing global health challenges, particularly in resource-limited settings. Through continued research and development, both Google and Salcit aim to improve health outcomes for communities worldwide.

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As pioneers in the startup VC ecosystem, Accel (formerly known as Accel Partners), with over four decades of experience, entered the Indian market in 2008. They placed their initial bets on a nascent e-commerce company poised to compete with Amazon. 

In 2008, Accel India invested $800,000 in seed capital into Flipkart, followed by $100 million in subsequent rounds. The VC firm went on to back some of today’s most successful ventures, including AI startups. “We’ve invested in 27 [AI] companies in the last couple of years, which basically means we believe these 27 companies will be worth five to ten billion dollars [in the future],” said Prayank Swaroop, partner at Accel, in an exclusive interaction with AIM. 

Swaroop, who joined Accel in 2011, focuses on cybersecurity, developer tools, marketplaces, and SaaS investments, and has invested in companies such as Aavenir, Bizongo, Maverix, and Zetwerk. Having placed careful bets in the AI startup space, he continues to be optimistic, yet wary, about the Indian ecosystem. 

Swaroop observed that while the Indian ecosystem has impressive companies, not all can achieve significant scale. He mentioned that they encounter companies that reach $5 to $10 million in revenue quickly, but they don’t believe those companies can grow to $400 to $500 million, so they choose not to invest in them.

Swaroop told AIM that Accel doesn’t have any kind of capital constraints and can support as many startups as possible. However, their focus is on startups with the ambition to grow into $5 to $10 billion companies, rather than those aiming for $100 million. “I think that is our ambition,” he said. 

Accel has also been clear about having no inhibition in investing in wrapper-based AI companies. They believe that as long as the startup is able to prove that they will find customers by building GPT or AI wrappers on other products, it is fine.  

“The majority of people can start with a wrapper and then, over a period of time, build the complexity of having their own model. You don’t need to do it from day one,” said Swaroop.

However, he also pointed out that for a research-led foundational model, it’s crucial to stand out, and that one cannot just create a GPT wrapper and claim it’s a new innovation.

Accel has invested in a diversified portfolio including food delivery company Swiggy, SaaS giant Freshworks, fitness company Cult.fit, and insurance tech Acko. Accel has made its second highest number of investments in India with a total of 218 companies, only behind the United States with 572. In 2022, the market value of Accel’s portfolio was over $100 billion.

Accelerating AI Startups

Accel has a dedicated programme called Accel Atoms AI that looks to invest in promising AI-focused startups across early stages. The cohort of startups will be funded and supported by Accel partners and founders to help them grow faster. 

Selected startups in Accel Atoms 3.0 received up to $500k in funding, cloud service credits, including $100,000 for AWS, $150,000 for Microsoft Azure, $250,000 for Google Cloud Platform, GitHub credits, and other perks. The latest edition, Atoms 4.0, is expected to begin in a couple of months.

While these programmes are in place, Accel has been following a particular investment philosophy for AI startups. 

Accel’s Investment Philosophy

The investment philosophy of Accel when it comes to AI startups entails a number of key criteria, that includes even the type of team. “It’s a cliched thing in VC, but we definitely look at the team,” said Swaroop, saying that they need to have an appreciation of AI.

He emphasised that teams must embrace AI, and be willing to dive into research and seek help when needed, demonstrating both a commitment to learning and effective communication.

Accel also focuses on startups that solve real problems. Swaroop believes that founders should clearly identify their customers and show how their solution can generate significant revenue.

“We get team members who are solving great things, and we realise they are solving great things, but they can’t say that. When they can’t say that, they can’t raise funding. Basically, are you a good storyteller about it?” he explained.

Revenue Growth Struggles  

Swaroop further explained how VCs are increasingly expecting AI startups to demonstrate rapid revenue growth. 

Unlike traditional deep tech companies that may take years to generate revenue, AI firms must show significant commercial traction within 12 to 18 months. He also stated that as VC investment in AI rises, startups without clear revenue paths face growing challenges in securing funding. 

“Even to the pre-seed companies, we say, ‘Hey, you need to show whatever money you have before your next fundraiser. You need to start showing proof that customers are using you.’ Because so many other AI companies exist,” he said. 

Swaroop also highlighted how investment behaviour for AI startups has changed over the last year where investors are now asking the hard questions.

VCs Obsess Over Data Moats

Speaking about what differentiates an AI startup and their moat, Swaroop highlighted how the quality of datasets may be a deciding factor; and “not so much” with Indic datasets.

“I don’t think language datasets can be a moat, because everybody understands language. Recently, in the Bhashini project, IISc gave out 16,000 hours of audio, so it is democratic data. Everybody owns it, so what’s proprietary in it for you?” asked Swaroop.  

Proprietary datasets, such as those in healthcare or specialised fields, are valuable due to their complexity and the effort required to create them. “I think startups should pick and choose an area where they have uniqueness of data, where they will have proprietary data which is different from just democratic data. That’s the broad thing,” said Swaroop.

Irrespective of the moat, India continues to be a great market with multiple opportunities for investment. In fact, at a recent Accel summit, Swaroop jokingly mentioned how he did not invest in Zomato during its early stage, but there are no regrets. Interestingly, Accel has invested heavily in Zomato’s competitor, Swiggy.

“I think the first thing you have to let go of as a VC is FOMO, the fear of missing out, that’s why I could not think of a company that I regret not investing in, because, my belief is that India is a great market. Smart founders come and keep on coming. We’ll have enough opportunities to invest in,” concluded Swaroop, excited to meet the next generation of founders working in the AI startup ecosystem. 

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