Sramana Mitra: Software development is getting hugely streamlined, right? The co-pilots are becoming extremely effective. So, you don’t need as many people on the software services side as well. There are a lot of co-pilot products that are getting sold into that business. So, there’s a whole market emerging out of efficiency in the software development ecosystem.
So, let’s talk a little bit about these companies that you mentioned as use cases and case studies of what you’re investing in. Cognida and Critical River are two that you just mentioned. Could you talk to us about what these companies are doing and how these models are playing into their situations?
Raju Reddy: These are more services companies, but purely on the product side, too. There are much more AI-first kind of companies that I’m involved with. Some of that is in the public domain.
One of the companies that I’m on the board of is called SciSpace, for example. That’s much more into accelerating research. Think of it as a much more modern version of Google Scholar that is getting very solid traction. We started monetizing just in October of 2023. We are at about five times where we planned to be by end of 2024. It has well over seven million users today. Just in the last 28 days, we’ve added a couple of million new users.
I think the takeoff and the traction is very real when you have a product that the market is looking for. I can go into each of these in more detail if necessary. SciSpace is a fantastic example of that.
Sramana Mitra: So can you talk more about SciSpace, Raju? What is the audience? Is it researchers and universities and academia? What is the audience?
Raju Reddy: Yes. Anybody who is doing research, publishing papers, or analyzing research papers to make their decisions. Academia, certainly, is a big part of it. But it could also be in the corporate world, like in the pharma or health care sector. There’re a lot of research labs in the world outside of what you would call normally just universities. They’re all customers for SciSpace.
It was started well before GenAI, specifically ChatGPT came into the marketplace. It’s more around ML when they started building it. But they certainly got a great tailwind here with GenAI becoming more commonplace now and with all the models becoming much richer. So, they’re able to deliver a much higher value of research capabilities for publishing research papers as well as doing deep research analysis on any topic that typically a research lab might be dealing with.
Sramana Mitra: Interesting. And you quoted some very big numbers in terms of customer addition. In twenty-eight days, two million customers added.
Raju Reddy: Two million users. Part of that is a fraction of the paying customers.
Sramana Mitra: How are people finding this? Is it all searching? Are people just finding through word of mouth?
Raju Reddy: Yes, it’s been mostly there. That’s the interesting thing, Sramana. We haven’t even started spending any marketing dollars. So, it’s been largely word of mouth and quite a bit on Twitter. I didn’t know that these scientists hang out on Twitter! They do, or at least they get their feed from Twitter. It’s been largely word of mouth, and it’s just been phenomenal.
Sramana Mitra: What else have you invested in that is interesting? This is very interesting, what you just said.
Raju Reddy: There are a few other companies. There’s one called Flam, which is, again in public domain. Actually, Google used them. It’s basically in the advertising space. It brings your print ads to life. It’s a mixed reality, but again, there’s a lot of AI within that. This is not necessarily GenAI, but AI.
This is a company that’s really caught on fire just in terms of how it’s sort of disrupting the advertising industry. Typically, print ads are a dwindling market, but just by taking your phone and pointing to the QR code in a print ad, the video starts playing within that frame.
Samsung recently introduced a feature called Circle to Search along with Google. They used Flam for that and several large enterprises have been using that. The product came into market about a year ago and the company is doing extremely well. Again, these are all young first-time entrepreneurs, whether it’s SciSpace or Flam.
One of the areas that I’m sort of spending more time now is looking at companies, not just at the application level. As more of the AI apps become a big part of the economy in the tech industry, I believe on the infrastructure side, there’s going to be a lot of strain or demand thereby for better performance, better reliability, security, and things like that.
So there is a company that’s kind of in a stealth mode, called AkashX, started by a bunch of these tech wizards coming from the database world that are building this. Essentially, all your LLM queries in the underlying layer translates into a bunch of SQL queries. So how do you execute those SQL queries much faster and with a higher reliability is kind of the problem that they’re solving.
But my point is, as a lot of founders and entrepreneurs are looking at how can I use AI for a certain kind of business problem, I personally think there are going to be a lot of opportunities at the infrastructure layer, given the sort of demands that these AI apps are going to put on the infra.
This segment is part 2 in the series : 1Mby1M AI Investor Forum: Angel Investor Raju Reddy
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