Bootstrap Lab Sees Massive Opening in AI for Energy: Q&A

By Danya Liu, BloombergNEF analyst. This article first appeared on the Bloomberg Terminal.  

Bootstrap Labs, a California-based venture-capital investor focused on finding startups that apply artificial intelligence to industrial problems, is turning its attention to the energy sector. The AI portfolio of Bootstrap spans health care, enterprise productivity, transportation, energy and engineering/logistics. It invests at Seed to Series A stage enterprises and is often their first source of institutional capital.

“We rarely invest in a company without deep AI expertise in the core team, that’s a top priority, as well as the team’s ability to learn and iterate fast,” founder and Chief Executive Nicolai Wadstrom said in an interview for BloombergNEF’s January Tech Radar.

Bootstrap has initiated a limited partnership with Innogy as they look to the energy sector for new opportunities. “We decided to enter the energy space because the opportunity is massive, Wadstrom said. “You’re moving from utilities owning the only sources of generation to literally every home being a producer and a consumer of energy. And that’s just one of the transformations the electric grid is facing. With renewables and peer to peer trading and electric vehicle charging, we will reach a point soon where humans aren’t capable of managing the grid anymore. We will need AI.”

Wadstrom’s comments have been edited for sense and flow.

Q: Give us an idea of your strategy and focus areas.

A: Big picture, there are a few pillars that make up modern society: agriculture, health care, energy, transport and cyber. When we first started ten years ago, we were looking at how software was creating exponential efficiencies in each pillar. Slowly we started to see machine learning driving the most exciting software, and when you combine proprietary data streams with cutting-edge software, you’re in an interesting space. So, in a nutshell, we invest in smart talent that addresses society’s highest-value problems.

We have two funds solely focused on applied AI, and will raise a third soon. Our two currently active funds are together $55 million, and we’re aiming for our third fund to be double that. We really like operating in the Seed-to-Series-A stage because that’s where you can offer the most value to your founders. If you go later stage, you lose out on some opportunities to help build and shape the company. And as an added bonus, good seed-stage investments have much higher return than you find later stage.

There’s a lot of talk about how AI is built, whether on the hardware or software side, but there was no real voice around how AI is applied – and that’s the step of real value creation. That was intriguing for us, especially as a VC, because we play well in that space of introducing and applying new technology. So we set about forming a community of industry and technical experts to explore how AI is impacting people, society and companies. We’re very proud to have this robust community and to help steer that conversation.

Q: Let’s talk about your investment process. Are you doing industry research to identify opportunities for AI?

A:
We take the view that we need to know a little about everything in order to understand the context, but we don’t necessarily deep dive into industry research. While that can be helpful, we find it’s more valuable if our assessments are anchored in our experience building and scaling technology companies. Our applied AI community is also key here. We have experts from around the world we can call on to help bolster our understanding, or check our assumptions. This community is a great resource for our founders as well. Some of our startups have brought on new advisers, recruited AI talent, secured new customers, or sourced additional capital all through this community.

Q: What do you look for in your startups?

A: What’s most important for us is to identify the top talent, so I’d say the core or founding team of a startup is key. As a startup, your technology is inevitably going to change as you discover product market fit. What takes you through that is the strength of your team. We rarely invest in a company without deep AI expertise in the core team, that’s a top priority, as well as the team’s ability to learn and iterate fast. We do not necessarily need domain expertise from the get-go, but like to see that come into the team at depth in the journey.

Q: How do you strike the balance between technology that’s cutting-edge and technology that’s industry-ready?

A: AI is an ambient revolution. If we’re talking about software, as far as end-users are concerned, not much will change. Your interface might stay sensibly the same while the backend of whatever program you’re using is upgraded with AI. Some industries like construction haven’t seen much use of data through the lifecycle of projects, so there’s a massive opportunity for efficiency improvement. We invested in a computer vision solution that quantifies construction progress, safety violations and predicts future timelines. They’re adding a layer of knowledge that didn’t exist before, and to a large extent, the behavior doesn’t need to change among the workforce. We are looking for chances to introduce dramatic impact but customers aren’t buying AI, they’re buying results. They don’t need to care that AI is delivering it.

Q: You recently brought Innogy on as a strategic limited partner and simultaneously entered the energy space. Could you talk about how you work together?

A: We decided to enter the energy space because the opportunity is massive. Here in California, there’s a law coming into effect in 2020, that every new home is required to have solar panels. So you’re moving from utilities owning the only sources of generation to literally every home being a producer and a consumer of energy. And that’s just one of the transformations the electric grid is facing. With renewables and peer to peer trading and electric vehicle charging, we will reach a point soon where humans aren’t capable of managing the grid anymore. We will need AI.

Together with Innogy we’re building the largest intersection between energy and AI in the world. Innogy is a very innovative company, they understand the electric utility space extremely well but they’re also looking out into other emerging areas. They’re bringing pain points to us and they help us understand the opportunities within energy. We look at deal flow together and keep each other updated on any new trends we see. We look at them as our energy partner, and they look at us as their AI partner.

Q: A lot of industries aren’t ready for AI today. For example, utilities face a rate-base hurdle. What type of groundwork needs to be laid first before AI can integrate into industry?

A: Yes, regulation is a challenge for utilities especially. There hasn’t been a lot of pressure to revise utility regulation in the U.S., but we’re seeing some of that change now, driven by concerns around cybersecurity, environmental factors, and reliability. How we help secure critical infrastructure with AI is something we deeply care about.

But keep in mind that for us, entering into the energy AI market doesn’t mean that we’re looking at utility applications exclusively. People are becoming ‘prosumers’, appliance makers are getting interested in energy usage. A lot of parties play in the space we’re building between energy, AI and data. So yes, utilities face a regulatory hurdle but our founders have a wide breadth of potential customers and opportunities to go to market.

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