Extending Product Roadmaps with Generative AI: Acrolinx CEO Volker Smid (Part 2)

Sramana Mitra: What did you do after?

Volker Smid: Fulfilled my lifelong dream to go to the US. It was in 2000.

Sramana Mitra: To what company?

Volker Smid: It was a US-German company that went public in the year 2000. It was called Poet. We had a marketplace catalog product, which was a big thing in the year 2000. Every marketplace needed to have a catalog and we were the catalog provider. If you remember 2000, it was a pretty crazy time.

Extending Product Roadmaps with Generative AI: Acrolinx CEO Volker Smid (Part 1)

In this conversation, Volker discusses how his company is extending its product line with Generative AI, and also, very specific new startup ideas leveraging the capabilities of Generative AI.

Sramana Mitra: Let’s start at the very beginning of your journey. Where are you from? Where were you born and raised? What kind of background?

Capital Efficient Strategy for Generative AI Startups: Aisera CEO Muddu Sudhakar (Part 4)

Sramana Mitra: The PaaS business is getting harder and harder to do because the big players are so entrenched. It’s so expensive. The stack is so expensive from an infrastructure and computing point of view. You can’t really play the PaaS game as a startup anymore. Let’s switch to what you’re seeing on the go-to-market side.

When you were doing the beginning phase of Aisera, AI was not in the mainstream. The demand in the enterprise for AI-enabled solutions was not as strong. Now, the conversation has shifted. C-levels are talking about it. This must be making life easier for you.

Capital Efficient Strategy for Generative AI Startups: Aisera CEO Muddu Sudhakar (Part 3)

Muddu Sudhakar: I run a PaaS company. I used to work for VMWare. We had the Hadoop stack and catered to Java. What happened is you have to optimize it to a cloud. You need to take your PaaS and optimize to one infrastructure. If you have a proprietary NLM, it’s not going to be specialized to Azure as well as Azure can.

I, as a vendor, have to make sure that my NLMs will run on more than one cloud provider. Customers may want multiple choices. The burden is on me to make sure that Aisera algorithms can run on AWS, Azure, and Google. I’m optimizing to each of the stacks and not going to 20 of them.

Capital Efficient Strategy for Generative AI Startups: Aisera CEO Muddu Sudhakar (Part 2)

Sramana Mitra: Let’s get into some of those questions. You mentioned Azure. Now, generative AI from the Microsoft camp is available on top of Azure as a PaaS for companies like Aisera to tap into.

Muddu Sudhakar: We partnered with Microsoft. We use their Azure Open AI. Our algorithms and NLMs are built on Azure.

Sramana Mitra: All the computing is happening on the Azure platform?

Capital Efficient Strategy for Generative AI Startups: Aisera CEO Muddu Sudhakar (Part 1)

Muddu Sudhakar and I share the perspective that the real opportunity for Generative AI startups is not in building platforms but in piggybacking on other platforms.

This conversation deep dives into the subject with real world examples and explores all the nuances entrepreneurs need to consider.

Capital Efficient Strategy for Generative AI Startups: RavenPack CEO Armando Gonzales (Part 6)

Sramana Mitra: How big a deal has your infrastructure been as a cost element in the past and now? It does take horsepower to process data.

Armando Gonzales: Because we don’t have access to that type of capital, we had to build a very cost-effective system. Even these days, it’s probably less than 10% of our gross revenues. Because of the type of software and infrastructure we’ve built, we are able to operate very efficiently.

Capital Efficient Strategy for Generative AI Startups: RavenPack CEO Armando Gonzales (Part 5)

Sramana Mitra: At this point, you had a customer. You understand your TAM. You are starting to execute. It’s an easier funding situation.

Armando Gonzales: Exactly.

Sramana Mitra: How much did you raise?

Armando Gonzales: $3 million.

Sramana Mitra: 2008?