The newest member of our investing team adds to Scale’s technical depth in AI and machine learning
I’m very happy to officially welcome Oana Olteanu to the Scale investing team. Oana is a native of Romania who studied machine learning and computer science before joining SAP in Germany. At SAP, she advised on go-to-market strategies for new products then joined SAP.io, the company’s $35 million early stage venture fund. An engineer by training with operating and investing experience, Oana has a really interesting perspective on AI and machine learning in the context of enterprise software.
Here’s more about her background and investing focus in her own words:
Andy: Quite a few of us on the Scale team were born outside the U.S. then made their way to Silicon Valley. You told me a great story about your move here from Germany...
Oana: I knew I’d arrived in Silicon Valley the moment I saw an Atari Middle Earth Pinball in the kitchen of the place I was looking to rent. I love Atari. The first game I played was Frogs and Flies around the age of 5 on an Atari 2600. And here I was in Silicon Valley asking the landlord about the pinball machine in the kitchen. Then it turned out that he had been the head of the microelectronics division at Atari and directly responsible for our family’s beloved 2600!
I don't know of any other place where rentals come with Atari games and the backstory of how they got created. I still try to find some time to play Pong even today.
Andy: Our team first met you when we invested alongside SAP.io in BigID. We saw right away that you’re passionate about machine learning. Where did your interest first develop?
Oana: In my last year of high school, I won the grand prize in a NASA competition to design a space station. It’s hard not to be interested in space when you grow up away from any cities with a perfect sky for stargazing without light pollution. I developed an interest in astronomy and was often on NASA’s website whenever I had access to the internet in the computer science lab. That’s where I saw the contest announcement, and I thought it would be a great challenge and I’ll get to learn a lot of new things as I figure it all out. The researchers must have appreciated the novel lighting system consisting of two conical mirrors and a fiber optics network, and the modular structure of the space station that combined a torus with the honeycomb shape for maximum security.
The result of winning the contest was that I got to visit the NASA Ames Research Center in Mountain View. The work I saw there in Intelligent Systems shaped my interest in computer science. I eventually wrote my Bachelor's thesis on using echo state neural networks for handwritten character recognition, back in 2010 when ML wasn’t cool. And I followed up on that with a Master’s thesis on machine-to-machine (M2M) platforms.
Andy: Like you, I was an engineer before I was a venture investor. What was your path into venture capital?
Oana: I am in VC to back people with unique insights into big problems. I got into VC at SAP.io, where I sourced and evaluated investments in enterprise software with a focus on AI. Two of the first deals I sourced were Plum.io, which uses neural networks to help companies with hiring, and Oto.ai, which is merging the modalities of words and intonation to build the next gen in speech technology.
Andy: What did you learn from your operating role at SAP that can be useful to founders?
Oana: There are three main takeaways that I like to share with founders.
The first one is how critical culture is in turning a small startup into a highly successful market leader. Everything needs to be done to ensure the core values are being lived as the company grows up and the challenges change.
The second takeaway comes from the work I did assessing the launch readiness of more than 50 new products at SAP. There are numerous best practices about how to properly build a Minimum Viable Product (MVP) by picking the right customers for product development, setting up an effective customer advisory board, focusing on business value rather than features, and selecting the right types of early customers.
The third area where I can help founders is around go-to-market readiness, in particular how to optimize for speed while securing the benefits of a GTM partnership with a large corporation.
Andy: I’ve seen firsthand that founders with technical backgrounds often welcome working with investors with technical backgrounds. What can the founders of AI and machine learning companies expect from you?
Oana: They can expect a break from having to explain over and over again how a real AI company works. Instead, we will have a deep conversation focused on data and the flywheel effect of data and model progress for production customers. We will also talk about their intimate understanding of what the user and the market want and will pay for.
I believe that having a true AI product, not just X with AI, that becomes available at a time of strong market demand, will enable them to grow into a wildly successful company. I like starting with a demo or playing with the product, as it provides the best context for the conversation.
Andy: What sorts of startups are most interesting to you right now?
Oana: I am looking for startups that are doing amazing, transformative things with AI. I pay special attention to startups that can show value from the get-go from products designed around a strong feedback loop.
I’m always looking to talk to founders whose companies have reached product-market fit and are ready to scale—though I’m also happy to connect a little earlier in their development to discuss achieving product-market fit.
With AI, machine learning, and other advanced technologies continuing to reshape the enterprise software landscape, we’re glad to welcome Oana to our investing team.