EQT’s Alexandra Lutz: Motherbrain will be ‘the backbone of the investment lifecycle’

Motherbrain allows EQT’s private equity dealmakers to become ‘smarter and faster at what they already do’.

Alexandra Lutz became head of Motherbrain, EQT’s proprietary investment platform, in January. PE Hub Europe recently interviewed Lutz about her plans to complete Motherbrain’s evolution from its origins as a tool for venture capital teams to becoming a platform for dealmakers in private equity and other sectors.

Alexandra Lutz: ‘Bringing the perspective of the end user’

Can you describe Motherbrain and your role on the team?

The important thing about Motherbrain is that it is an internally incubated AI, machine learning start-up, that does incredibly powerful things with data. My role now is to help infuse everything we do with an understanding of how our deal teams operate – what they need, what the rhythms are of diligence. I’m bringing the perspective of the end user. You read a lot about AI and people think it’s magical. But it is always best when trained on a specific use case that has the end user in mind.

How did Motherbrain get started?

Motherbrain has been around for about five-and-a-half years. A very specific question was asked by the ventures team: in a world where hundreds of start-ups are founded every week, how do you find that proverbial needle in a haystack? The thinking was that there is so much you can know about a company from external data signals.

Motherbrain would use these ranking algorithms to put companies in front of the deal teams, which would then weigh in. That’s the magic of how it works – you’re taking external data and marrying it with internal proprietary data on people’s judgements, people’s assessments, people’s evaluation.

Motherbrain stayed in ventures for a couple of years, expanding beyond sourcing. It helps the ventures portfolio with finding talent, metrics, benchmarks and tracking their competitors.

How has Motherbrain evolved?

We’ve moved over the last year and a half to supporting all private capital and infrastructure. We now have three main use cases. The analytical lens is about how to help deal teams identify opportunities faster than their competitors and help them monitor a long pipeline. Private equity already know the companies they want to focus on. But there are only so many that they can very actively follow. We help them monitor the longer pipeline via data signals, proxies for growth, proxies for momentum.

The second area is this idea of connective tissue. At EQT, we have everything from private capital to ventures, from growth to private equity. When we are tracking companies in our pipeline, we attach to them notes from Slack channels – the deal team’s back and forth about interesting intel or what they heard from the management meeting. We attach our internal advisers, so people can see which advisers worked on which deals with which deal teams. The private equity portfolio team can see what we thought about a company when we looked at it in the growth portfolio.

The third part is taking all the power of the tools that we built for ourselves and putting it into the hands of the portfolio company. We’re creating interfaces and other ways for them to access the power of the data to monitor their own competition, identify add-ons and so on.

Are you seeing the same returns in the other parts of the business as you saw in venture capital?

Motherbrain takes large, unstructured data sets and makes sense of them without manual intervention. That’s more about getting deal teams to conviction faster – making sure before they even walk into the management meeting that they have a pretty deep and detailed view of this target versus its competitors. It’s also about positioning EQT to be a preferred buyer for a partner. It’s harder to say the specific value is ‘X’, because it’s about making deal teams smarter and faster at what they already do.

This is an area of opportunity for us. With the model we have for add-ons, you load the information, pull from all the data sources and come up with this dynamic list of companies. The data science team will put in front of the deal teams the things about which the machine is most uncertain, because they want human judgement to come in and help refine the models.

But I want to put the things that they know will be correct in front of them first, so that they understand it, believe it and trust it. Then over time, we pull in their insight to help teach the model more. This is the biggest thing as we moved from ventures into private equity and infrastructure. It’s understanding how deal teams think and understanding how we unlock them and give them value.

What are your longer-term plans for Motherbrain?

Motherbrain is going to be the backbone of the investment lifecycle. Private equity is in sectors. Growth is in its own sectors, but they’re basically subsectors of PE. If you think about technology, venture teams look at really early stage neobanks, emerging payments companies and cybersecurity companies that have new and unproven business models. Growth is looking at fintech, at the first generation of venture companies that have been successful and are further on in their evolution. PE is looking at technology.

You can connect the expertise across these different fund strategies. It doesn’t mean that PE is going to acquire a company that ventures was looking at, but they understand how ventures was thinking about the development of the sector. If you’re going into cyber insurance, did growth look at a company that was in this sector two years ago? If so, you have that all in one place as your starting point for a deal.

I want to say that in two years’ time, we will be supporting all EQT investment advisory professionals.