1Mby1M AI Investor Forum: Shripati Acharya, Managing Partner at Priven Advisors (Part 1)

Shripati Acharya, Managing Partner at Priven Advisors, discusses his firm’s AI Investment Thesis. We have a very strategic discussion on SaaS, Marketplaces and Agentic AI.

Sramana Mitra: Good morning, everybody. Welcome to today’s One Million by One Million strategy round table for entrepreneurs. 1Mby1M, as you know, is the first and only global virtual accelerator for technology startups. Our mission is to help a million entrepreneurs reach a million dollars and beyond in annual revenue.

This is our 679th Roundtable. We’ve been doing these roundtables since 2008. It’s been many, many, many years, months, weeks, days of being on deck doing this, and hundreds and hundreds of thousands of participants have made this program successful and valuable. We still have no difficulty getting people to come and discuss their businesses.

It’s been a tremendous learning experience for me too, because everybody knows something about a domain that I don’t necessarily know that much about. I know a lot about how to get businesses going and put one foot before the other, but there are many, many domains where we get domain experts coming and talking, and it’s fascinating to hear.

We are going to start today’s session with a conversation with Shripati Acharya. Shripati has been here before. He’s the Managing Partner of Priven Advisors, and we have a very interesting discussion on AI strategy for his firm.

AI strategy is something we’ve been discussing quite extensively for a while now, because pretty much the whole startup ecosystem is buzzing with AI. There is a lot of confusion. Some things are becoming clearer, some things are still not clear. So, there’s a whole lot of issues to work through. Shripati, we are looking for your wisdom to help us do that.

Shripati Acharya: Thank you so much, Sramana, for having me here. It’s a pleasure, and congratulations again for what you have created here and accessing so many entrepreneurs.

I’d be very happy to share my thoughts; I wouldn’t go as far as to say wisdom but definitely happy to share my thoughts.

Sramana Mitra: Let me start with getting your general framework of how you are thinking about AI investments from your firm. What do you think are the most interesting areas of entrepreneurship and what are you looking for? What are you investing in? Let’s look at some case studies and we’ll do some deep dive into agentic AI, in particular, because that’s obviously top of mind right now and kind of hot off the press. So, let’s start with the general framework.

Shripati Acharya: Okay, wonderful. So, this is a framework which we use. Different folks have different ways of slicing this foundational, very transformational event in the history of technology. Some folks have compared it to invention of electricity and so on and so forth.

I would say it [AI] is probably as relevant and important as when the internet became usable with the launch of Netscape browser. It’s definitely as seminal as that.

So very simply, the way we look at it is that at the bottom, we have the foundational models, and these include ones from Anthropic, OpenAI, Gemini, etc. After that, you have a middleware layer which is connecting these models and all the applications which are going to be built on top of it. Then of course, at the top there are the applications themselves, with which the end users are interacting and typing into these. It could be any number of things, which we are all very familiar with.

The way we think about this is that obviously it’s a funnel in the sense that the largest number of opportunities will be on the application side, slightly lesser on the middleware side, and of course, even lesser on the model side in terms of the number of successful companies out there, not necessarily the size of the pie.

Clearly, the number of foundational models, which are going to be out there are going to be very few. You have Anthropic, OpenAI, Gemini, and so on and so forth. Of course, a bunch of open source models are rapidly gaining steam, DeepSeek being one of them.

Then on the middleware, there will be more things which are actually stitching things together, and on top you have the applications.

The obvious thing is in investing in applications, which are going to get reinvented in an AI native world.

So, it’s a little bit like thinking that we had an application before the net, which is client server sitting on PCs, and every application got reinvented in the web world. Similarly, every SaaS application can be safely thought, and correctly so, to be reinvented in the AI world.

The question is, what makes for the most interesting applications to invest in on the app side? This is how we are thinking about it. This might sound a little oxymoronic – we want to invest in opportunities where the technical AI component is actually a small part of the overall solution.

Let me unpack what I mean by that.

So, if you’re sitting in an enterprise stack and providing enterprise solutions, any AI application will be sitting on top of the model. The fundamental question that you ask is that when the underlying model becomes way better than what it currently is, which we can all safely say in five years’ time, it’ll be, what is the persistent value add of this application? Does it actually diminish or does it increase, or it remains the same? Obviously if it diminishes, I think it’s less compelling an investment, even if the current traction appears very high.

What that means is that when we are looking at applications, if they’re sitting inside an enterprise, they’re integrating with a lot of existing enterprise applications, which are integrating into the existing enterprise workflows, which are already there, where the current user persona is using it, it’s not actually causing a change to that, but just enhancing it.

When the entrepreneur understands the selling process and how that current product is going to fit in the existing budgets of enterprises, it makes for a compelling value proposition.

When we look at it, you’ll find that the actual AI piece of it is critical and important, but it is a very small part of the overall value proposition you’re delivering to the customer.

So that’s how we are looking at it. And these tend to be vertical solutions. They tend to be solutions which are in specific industries.

That is the framework here, Sramana. I can illustrate as an example, but I’ll just pause here for a second.

This segment is part 1 in the series : 1Mby1M AI Investor Forum: Shripati Acharya, Managing Partner at Priven Advisors
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