1Mby1M Virtual Accelerator AI Investor Forum: With Yash Hemaraj, General Partner at BGV (Part 1)

Yash Hemaraj is General Partner at BGV, and Founding Partner at Arka Venture Labs. This is a very interesting discussion that goes into the nuances of high velocity Positioning and Go To Market strategies.

Sramana Mitra: Good morning, everyone! Welcome to today’s One Million by One Million (1Mby1M) Strategy Roundtable for Entrepreneurs. As you know, 1Mby1M is the first and only global virtual accelerator for technology startups. We’ve been running this program for a long time. 1Mby1M launched in 2010, and as part of our mission, we host these free roundtables almost every week. In fact, we’ve been doing them since 2008. This is our 652nd session, so it’s been quite a long journey. Over a quarter of a million people have participated in these roundtables. We also regularly invite investors to discuss their investment theses. Especially when new trends are emerging, we invite investors to help us think through how they are processing the market trends.

For those of you who’ve joined us in the past few weeks, we’ve been working on AI investment theses and had some fascinating conversations. Today, we’re excited to continue that dialogue with Yash Hemaraj, General Partner at BGV and Founding Partner at Arca Venture Labs, which is BGV’s accelerator in Bangalore. Yash, welcome.

Yash Hemaraj: Thank you, Sramana. It’s a pleasure.

Sramana Mitra: Yash, let’s start with an overview of how you and your partners at BGV are thinking about AI investments—what trends and developments are you observing in the market?

Yash Hemaraj: Thanks again for having me. I’ve been with BGV for about 10 years now. Before joining the firm, I worked on building indoor wireless networks, so I come from an operational background. Around 2018-2019, we created Arca Venture Labs to help Indian founders scale their businesses from India to global markets.

We’re primarily early-stage investors and focus on enterprise AI—investing in enterprise technologies that transform industries. We also back cross-border companies that are built in innovation hubs like India and Israel and help them expand to the US.

Our core thesis revolves around enterprise technologies, and AI is undoubtedly a force multiplier. We’re seeing massive AI adoption across multiple industries. Even in the early days—around 2016-2017—we noticed that machine learning (ML) and computer vision techniques were becoming democratized and widely accessible. We saw the potential for AI to transform businesses by improving productivity, efficiency, and cost savings. However, we realized that while AI is a force multiplier, it doesn’t penetrate enterprises on its own.

Take, for example, a factory floor worker. They’re more concerned with how to perform their tasks efficiently and go home on time, not with how AI works. Early predictive technologies were useful, but now the technology has evolved to be more actionable. The key is to embed AI into existing workflows, helping people perform their jobs better.

One major element we focus on is workflow automation. It’s crucial to understand the tasks people perform daily and how AI can assist them in doing those tasks more efficiently. For example, if a factory worker is running out of inventory, it’s not enough to show a prediction that stocks will run out soon. AI needs to provide actionable insights—how much inventory to order, when to order, where to order from, and even implications in terms of delivery time, cost, and carbon footprint. So you need to provide the right information at the right stage of the workflow and help them execute it.

Another important element is data. Many companies try to boil the ocean, gathering vast amounts of data and searching for the proverbial needle in the haystack. But we’ve found that when you integrate AI into workflows, you can focus on collecting the right type and volume of data. This helps models converge faster and improves outcomes.

So, our thesis revolves around the combination of AI techniques, workflow automation, and data. When you integrate these into a full end-to-end solution, that’s where the real magic happens—where we see the true benefits of AI in enterprises. Before the advent of generative AI, we called this approach “Enterprise 4.2” technologies, focusing on AI-powered workflow automation in vertically integrated solutions.

With generative AI, the landscape has expanded dramatically. Machines can now process much larger volumes and more diverse types of data driven by huge investments into GPU clouds. As a result, their capabilities in data processing and execution have multiplied. But for us, the key is still the interplay between humans and machines. It’s about how human ingenuity combined with AI can transform industries. We now refer to this as “Enterprise 5.2”.

We are very excited about where this is headed. We’re seeing companies disrupt legacy industries and automate enterprise functions—initially through AI-powered co-pilots and, eventually, fully integrated AI agents. It’s an exciting time for AI in the enterprise space.

This segment is part 1 in the series : 1Mby1M Virtual Accelerator AI Investor Forum: With Yash Hemaraj, General Partner at BGV
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