It is my pleasure to announce that Patrick Pichette has joined the Neo4j Board of Directors. Patrick is a partner at Inovia Capital, former CFO at Google, and currently the Board Chair at Twitter – to say his experience and leadership is a phenomenal fit at Neo4j is an understatement.
Patrick and I had a chance to sit down and talk about his illustrious professional background, his experience with graph technology on a massive scale, his vision for the future of Neo4j, and our respective Nordic camaraderie.
This is a match made in heaven and I invite you to jump into our conversation as it unfolded.
Emil and Patrick: In the Beginning
Patrick Pichette: Emil and I got an intro through a trusted advisor in our investor network. In the business community everybody talks to everybody – we have our own network of really trusted investors. And they said, “Hey, we’re just closing a round with this great little company. You may have heard of them.” They talked about Neo4j and it just happened that Neo4j was on our top 10 list of companies to reach out to.
Emil Eifrem: Wow, I actually didn’t know that.
Patrick Pichette: When we do outbound, we think, “Which company will fit with us?” Rather than there’s a round coming and therefore let’s go and hunt. That’s just not how it works, because we are capacity-constrained. And if you’re capacity-constrained, then you say, “Who do you want to work with?”
So, it happened to be on our list and as you know, Emil, through them, we reached out to you to say, “We heard you did a great round, so congratulations. We’d just love to hear your stories, so that if there’s another round later, maybe we’ll be there.” That was actually the genesis of the conversation. What was really amazing is we finished this first chat and both of us thought, “Wow, that was a good conversation.”
Emil Eifrem: Yeah, totally.
Patrick Pichette: Then we said, “Okay, let’s think about it.” And then a couple of days later, I don’t know who called who, but it was just like, hey, maybe there’s an opportunity here. Emil was just closing the round, instead of having closed the round.
Emil Eifrem: Yeah, we announced the round on a Thursday at our big event NODES 2021, our big developer conference, and literally the day after Patrick and I had our first call. It was from a guy we really trust. The combination of that and your unique background, both of them had to be true in order for me to even think about taking a conversation with an investor the day after announcing the round – because I probably had peak fundraising fatigue at that point. And then that first conversation was just really low guard, authentic, and real.
What Made Our Connection Unique
Patrick Pichette: The big lesson here, to me, is that in the VC world there are all of these canned processes: Here’s how you do a round. And I think this is a great example for the entire community to take a step back and say, “Hey, go through first principles. Find people who are kindred spirits. Find people who share your values, and find people who you think, Wow, you see opportunities to really collaborate and grow together. When you find those, don’t worry about the process too much – just start. That’s the moment that this process should start, by being creative rather than handcuffed, which is a great example in this case.
Emil Eifrem: I couldn’t agree more, and the only thing I would add to that is what you said before, which is that in this world everyone is connected. There are networks everywhere and – of course, as a graph guy – I look at that, the value of those relationships, and the fact that we had this mutual person introduce us. Then when we got on the call, it turned out we had a bunch more mutual friends who just participated in the round.
Patrick Pichette: Absolutely. That’s why, again, don’t underestimate as a young entrepreneur or as a young person starting your career, the value of investing in networks. Invest in that graph, right? Because you never know. You just don’t know who’s going to end up where. Maybe 30 years ago, I was asked by the government of Canada to be on the board of a new foundation they were setting up, and it was called the Pierre Elliott Trudeau Foundation for the late Prime Minister.
Their first CEO was a professor at McGill, who had left academia. Anyway, 30 years later he gives me a call because he knows I’m in England, and he became the Vice Chancellor of Cambridge. You don’t know that when you’re 31, right? You just don’t. Then you’re friends for life and you interconnect through life and the value you bring to each other is absolutely immense.
Why Inovia Wanted to Invest in Neo4j
Patrick Pichette: Let’s go back to a principle I talked about a minute ago, which is that we’re capacity-constrained, which has disadvantages. Capacity, in terms of money, we have. We have this pot of money for us to find great companies that align with our mission, and then we support each other in growing.
How Inovia thinks about it, is that we look for companies that have these basic attributes. One is they have to have a global mindset. Although we’re Canadian-based, the question is: Will this tech solve a global problem? Then second is: Is the tech used for good? Which is really fundamental to our values. Good can be defined as many things, of course.
Productivity is good. When you’re selling lamps, and you sell them for $70, and through technology and productivity you can sell the same lamp for $40 and give the pleasure of your lamp to more people, I’m okay with that. That’s why we have this investment in Lightspeed retail, which I think enables every one of these little mom and pop stores that have High Street positions, as an example, to actually have the same boxing gloves as Amazon. I think that’s good, because cities that have no shops are dead cities. That’s where people live every day, right? So global mindset; technology for good.
In the case of what I particularly like, personally, with Neo4j is this combination of nonprofit and profit all mixed together in a can. The platform itself enables academic research – enabled with all the machine learning tools that are available today – a completely new avenue for life sciences and social sciences, and really thinks through new areas of academic development for amazingly good, which may or may not contribute on a for-profit basis. But it just has a massive impact for the world. That’s true also for the for-profit world. So a platform that hits both actually doesn’t show up that often.
Then what was really interesting to me about Neo4j, lastly, was the company is at a crossroad. It’s at a crossroad, in the sense that we’ve nailed the enterprise space on premise. The world has evolved in a way that cloud now is the architecture of tomorrow. In the cloud, the benefit is the addressable data is now infinite, literally. We also have an opportunity that every small and medium business needs these tools to compete and to actually have amazing advantages for themselves as well. So, there’s just these big vectors of growth that are right there on the doorstep of the company. They’re quite a lot of work, but they’re all there. The first decade of the chapter has been incredibly well written. Now you turn the page and there’s a completely new chapter to write.
To me, that’s really exciting. And when you put it all together it makes a hell of a case for investing in Neo4j.
Emil Eifrem: I love that. I’m dying to comment and go deeper into all the different things, but I’m trying to hold back. I think that was super well said.
How Patrick Will Help Power Neo4j’s Growth
Emil Eifrem: This is the “making Patrick blush” moment. I think there are a couple of things. Maybe there are three categories that convinced me to drag myself out of the fundraising fatigue and actually engage in this thing.
Patrick Pichette: One more time, with feeling!
Emil Eifrem: Exactly, exactly. “Once more unto the breach, dear friends.” So, the obvious one is skill set and background, and again, I don’t want to make you blush here, Patrick, but the background is just unique. Just your story at Google – it’s absolutely a once-in-a-lifetime opportunity to be able to tap into that experience. Double-clicking a little bit more on that, as a graph guy it’s just impossible for me not to weave the narrative around the fact that the core innovation of Google was a graph algorithm. That is what PageRank is. A well-known graph algo called eigenvector centrality, applied brilliantly to the web.
Then, I mean we’ve touched on this already, in that first conversation we talked a lot about how Neo4j can genuinely be a force for good in the world. It felt extremely authentic and a huge part of my reference checking on Patrick was that: Give me examples where Patrick has chosen the right thing to do when it’s not the profitable thing to do.
That’s the really hard stuff. It’s not hard to do the right thing when it also increases your revenues, right? The thing that is tough is when we know what the right thing to do is, but it’s profitable to go in the other direction. Even with people who are deeply ethical, it’s very rare to find examples of that, and I found plenty in my reference checking on Patrick. So that’s the second one.
Then the third one is just chemistry. We genuinely hit it off in that first conversation and it’s continued ever since. That fundamental alignment and the relationship piece was the third factor.
The Northern Nordic Camaraderie
Patrick Pichette: I think it’s worth noting our Nordic roots. I think there’s a lot to say about Canadian roots and your Nordic roots. These people from the North, they’re just different. I don’t know what it is, but there’s something in the water up here.
Emil Eifrem: I think that’s spot on. There was one time when I was getting on a call with Patrick and there’s a big-ass moose head in the background. And I don’t blink, because of course there’s a big moose head in the background. On another call, there’s a pair of cross country skis in the background. I don’t blink, because of course there’s a pair of cross country skis in the background.
I think that’s fun. It’s something in the water, in that pseudo-socialist upbringing. I think there’s something there that probably helped with that personal chemistry, the spiritual alignment.
Patrick Pichette: It was a great conversation, actually.
Emil Eifrem: Yeah, the foundation is really strong.
The Value of Democratizing Graphs for Business and for Good
Patrick Pichette: What’s interesting is one of the key successes of Google, one of the key powers, is to give small and medium businesses the same reach as very large businesses through technology. If you take a step back, this ad system – I’m going to make a very Canadian caricature: I used to sell maple syrup locally in my little shop.
You have your little maple syrup shop somewhere, right? Then the internet shows up, and then through the internet, through ad words, you can actually now sell your maple syrup all over the world. If you have a better value proposition, you can actually pay for the right keywords to really open the whole world to you and completely transform your business, for the benefit of everybody. People in Japan now buy maple syrup; it’s kind of a delicacy there.
Before Google, that wouldn’t have happened – it would have been way too complicated. Now, Amazon has figured out a different way, but my point is there’s a fundamental change. At the heart of it, it’s giving these little businesses a ton of power that they wouldn’t have otherwise, and I think that graph technology is – if you think about most businesses today and with the rise of everything digital – data is exploding everywhere. We all know that. It’s all these small businesses that have a ton of data, many of them should share with other small businesses so they have even more power to understand.
But no one knows how to harness, harvest, and actually get real value out of this data that they have. That’s still the holy grail of most SMBs. To actually be able to give tools that really completely transform the way they think of their businesses. They don’t need 50 different new areas, but just basic areas of better data mining and better – like these very simple cases that we have already at Neo4j – which is a better recommendation engine. Just, better. There’s value on both sides of this equation. If I’m trying to buy a pair of hiking boots, and then I have a really good recommendation engine suggesting people who bought these nice boots also bought these particular hiking poles – there’s smarts about it. That is so valuable for everybody, because there’s no sense of me getting a pair of subpar hiking poles and then having to return them. That’s a waste for everybody. To me, driving insights from the data and giving it real value – the big organizations, we don’t need to sell them. They already got it. It’s a how rather than a what.
In the case of SMBs, we’re still at the “what” phase, but there’s this immense opportunity to plug and play and get them really simple areas to go and explore. Commercially, I think this is an amazing opportunity.
In terms of graph technology and what I’ll call the nonprofit world (think of research and academia and journalism, all of the areas we need to continue to thrive), I think all of these research institutions and public intuitions – from the Panama Papers, we just had the Pandora Papers – these are just two perfect examples of the fact that it’s not enough to have the data if you can’t make a story out of it. Then you don’t know the implications. If you don’t know the implications, then you don’t know what you should do as an action agenda. I think that Neo4j is a perfect platform for what I’ll call, “killer use cases.” I think that, as we just said a minute ago, there’s 10 years of work to do. But in 10 years’ time when we look back – I hope, let’s put it on a little napkin, write it down, and then see in 10 years. We should bring it back and see if anything happened.
I would love that two types of cancer and three new drugs that are just genuinely consequential to the world have been found on the Neo4j platform. I would love to have political experiments of transparency for the administration of cities, provinces, or countries that have actually been set on Neo4j infrastructure for discovery, and then highlighting from a transparency perspective the good agents and bad agents. I think that would be an amazing feat for the world to explore the next type of transparency in government affairs or journalistic affairs.
Then, if we had a world where – I’m going to paint a picture just to make the case that every SMB that has a presence on the net has 20% less waste, and 20% or 30% more revenue that is really driven by, “I got the right product at the right price at the right time, that actually really fit because I shared it with the right set of networks.” It fuels into a better answer for everybody. There’s a massive productivity gain and a massive profit to be made from these infrastructures. To me, that’s kind of what I expect. That’s the opportunity, and that’s what I expect to see.
The Visionary Element
Emil Eifrem: I think you said that extremely well, Patrick. I want to go back to your former employer Google for a moment. Larry and Sergey did something very profound to their industry – web search – back in the ’90s at Stanford that is now happening to all industries: they reimagined it around connected data. Larry and Sergey said, “Wait, why are we ignoring how things are connected? The web is a massive connected thing. Why are we ignoring those connections when we search the web? Let’s build a search engine that ranks results based on how they’re connected, based on the graph of links between them.” That simple but powerful idea was the first step towards creating Google.
Patrick Pichette: In that statement, there are really two levels. The PageRank, which in 1999, is really a graph but on links. But there’s a second one, which was just as dramatic, because I was there when we launched the knowledge graph and the discussions about it. It was like, “Okay, that’s real compute.”
Emil Eifrem: Yes. What that’s called in the graph world is, you go from a “single-relational graph” to a “multi-relational graph.” It’s not just that we’re connected, but it’s how we’re connected. Which, if you look at life, is so important. As we’re recording this, the door just opened downstairs, and Madelene and my kids walked in. Knowing not just that I’m connected with Madelene, but that I’m Madelene’s husband, that I love her, that’s a very crucial thing. Are we friends, are we colleagues? How things are connected is an important aspect of turning data into insights and information into knowledge.
So getting the idea that you can reimagine your industry around how data is connected is the first step. The second step then is to figure out how to build the tech – the platform to process and operate on connected data at massive, global scale. Which is deeply, deeply hard to do. That is the second brilliance of Google in the early days, building the capability to do that. And as the CFO, Patrick, you funded, you’d know the numbers, but probably something like 40 trillion dollars every year of PhDs in computer science to build that graph processing technology platform from scratch. And those two things together, the idea and the technology platform, created Google.
That was over 20 years ago. Fast forward to today and the second part, the technology platform, is available to anyone. For example, back in 2016 a very small team of a dozen or so journalists got together when they received the Panama Papers data – the biggest leak in data journalism history – and they unpacked it and made sense of it. They created stories that shook the world. Prime ministers resigned and the journalists were awarded the Pulitzer Prize.
Why? Because their small team of developers and data journalists had access to this off-the-shelf Neo4j graph stack that allowed them to tap into the power of the GooglePlex for that data. And we just saw them repeat that trick with the Pandora Papers last month. I believe that extending the power of the GooglePlex to data journalists everywhere, democratizing access to that, has an amplifying effect on society at large. And that’s very inspirational to us here at Neo4j.
The Simple Complexity of Knowledge Graphs
Patrick Pichette: The reason why the knowledge graph was so amazing, I always come back to my Mona Lisa example.
Emil Eifrem: I haven’t heard it yet.
Patrick Pichette: So this is how I actually sold the story in 10 seconds. I said, “Let me tell you the difference between PageRank and knowledge graph.” In the PageRank world, when you typed in Mona Lisa, you had seven links, seven blue links that would bring you to Wikipedia and it would bring you to the next article that had the most quotations on the Mona Lisa. That’s what you had in the first seven. Probably no ads. The knowledge graph, when you type in the Mona Lisa, you get a picture of the Mona Lisa first. Then next to it you have the history of the Mona Lisa. Under it, you have topics like the Renaissance, you have Michelangelo, which is related to Da Vinci, and you have the entire cosmology. You have Venice, you have Florence, right? Which are all of the artifacts that are surrounding – and the connectivity – around one word, which is the Mona Lisa. That complexity brings a richness that’s absolutely extraordinary to find better answers. That is the difference between PageRank and knowledge graph. That’s what I mean by it’s such a huge step function, and if you run your business with an Oracle database, you’re in the PageRank world.
Emil Eifrem: At best! At best.
Patrick Pichette: At best. But if you live with your business in the knowledge graph world, that’s the step function that you would expect from it. That, to me, is the power of graphs.
Emil Eifrem: I’ll have to riff on that even more. Yes, searching for “things, not strings,” was how it was marketed. A brilliant way of summarizing it.
Patrick Pichette: Exactly.
Emil Eifrem: My example used to be, especially when I was in London, because we used to do a conference back when conferences were held at QE 11, which is of course a conference center, but Queen Elizabeth is also a person. Being able to disambiguate that and get the actual QE II “the building,” and –
Patrick Pichette: And a boat, by the way.
Emil Eifrem: I’m sure it’s a whiskey, too! The other really amazing trend that you must have seen firsthand inside of Google is something that we see in the broader enterprise today. And it’s that the initial way for Google to use its knowledge graph was to provide a visual navigation for the end user, the people searching Google, to navigate the knowledge graph on the right hand of a Google search like you just mentioned. Very powerful.
But the next step for Google was then to use that as a signal into their machine learning. Graph-based machine learning and Google started talking publicly about what a rich source of signal that graphs was for their machine learning. And we see that trend now playing out in the enterprise, in our broader customer base. They start with more simple, single relational graphs, the PageRank equivalent.
Then they add a knowledge graph, and initially the consumers of that are people, internal analysts, or end user customers. But then over time, what the really advanced companies want to do is start using the knowledge graph as a source for their machine learning. That’s one of the huge promises of this decade for graph technology: bringing other people along that Google journey.
The Future of Neo4j with Patrick on the Board
Patrick Pichette: With Neo4j, I want to change the world. I think that Neo4j has an amazing vision. I think they’ve demonstrated through our due diligence the quality of the people we met. You look ahead and you’re like, “Holy crap. There’s a lot of work to do.” We just need to step up, and just like every company, as you go up and write the next chapter, you’ve got to staff for the next wave, not for yesterday.
Strategically, so many issues will come our way without losing a beat. Because these things are about momentum as well – you just want to make sure that the world is indoctrinated to think in that way, to give them the tool that actually amazes people every step of the way – it’s a bold agenda. I think, to me, all the pieces of the puzzle are there. What do I look most forward to doing? We have a very clear agenda, and it’s about bringing traction to that agenda. Me as a board member, bringing all of the weight. Emil talked a lot about me at the front end, but Inovia is a small firm that punches way above its weight.
Emil Eifrem: Small firm with a powerful graph.
Patrick Pichette: Exactly. Not only a powerful graph, but we have Steve Woods who’s now our operating partner and head of tech, and just an extraordinary human being. The same thing with Dennis [Kavelman], the same thing with Karim [Sharobim]. So bringing not only the graph but just the weight of all of our resources to make sure that we just have fun doing it, instead of scratching our heads all the time. That’s basically what I’m looking forward to. Then, trying this famous Swedish July, June pole.
Emil Eifrem: The Maypole, yeah.
Patrick Pichette: I’ve got to do that once in my life, so I’m looking forward to that.
Emil Eifrem: That will be a blast for me, for sure. As for what I see in the future, Patrick said it well. I think I’d summarize it as the journey. I believe the opportunity is amazing. I think the challenges to get there are equally amazing, and I look forward to partnering up with Patrick and Inovia to tackle them. And enjoy that journey towards creating an impactful company that lasts for generations.