Will Marshall: Yeah, I mean, look — thank you for raising this, because I mean it is — we’re seeing this sort of regulation from the EU, in particular the EUDR, the deforestation regulation that is looking at importing of commodities and ensuring that they don’t cause deforestation as well, there’s not many ways, at least, at scale that you can do this without our dataset. And our dataset is primed to check whether or not a commodity from a source is causing deforestation or not. So, how we plan to it, to answer your question is really, we have many agricultural companies that we’re working to — with who are trying to address this and how they will meet their regulatory requirements under this Act, which by the way I think comes into force next year.
So it’s not like — it’s not that far away. And the scale of the proposition, really demands our solution. Also though, we can work with the regulators themselves, which is the other side of that, because of course they want to check that the companies are doing what they say. So, we can play both sides of that.
Jason Gursky: All right. Okay, great. I’ll pass the line. Appreciate the comments.
Ashley Fieglein Johnson: Thanks, Jason.
Operator: Thank you for your question. [Operator Instructions] Our next question will come from the line of Trevor Walsh with JMP Securities. You may proceed.
Trevor Walsh: Great, thanks, team, for taking my questions. Will, maybe for you. From your prepared remarks, you mentioned the unfortunate kind of, I guess, uptick or at least deals coming off of some of the natural disasters that we’ve seen lately, whether it’s fires in Maui or hurricanes and fires in Canada, et cetera. Do you get a sense or feel that those are state and local governments being very reactionary in their kind of use of turning to Planet for the data that you can provide to help with those types of issues? Or do you also see governments taking a more proactive nature to sort of bringing your solution beforehand before the problem actually becomes a problem? Just like to hear your thoughts on kind of if that’s more of a kind of a one-off thing or something bad has to happen first for there to be an action taken.
Will Marshall: Well, look, governments are beginning to see the value of this to really help them both in the response and prevention. Let me just touch on a tiny bit in the Maui case, I mean, which was just a terrible event. Our maps really helped in practical way. So, the Red Cross was using our data on the ground, in particular the map of all the building damage, as well as Hawaii state officials and even the President had a map with our — our map in his hands when being briefed on this. So, across the board we’re seeing real use of that data. And it’s also, by the way, a great example of how AI can play a part, because this is making that data more useful for the people on the ground. It’s not just a picture, it is a map of the building with the damage and that can help in quick response and prioritization on the ground.
But to your point — and one more point on that, the Canadian wildfires we’re seeing a similar sort of reaction and that’s why those — there were those three customer deals in Canada that I mentioned in my prepared remarks. But to your point about prevention and I think that’s a really critical one, we can do work to help civil governments prepare — prevent and prepare for disasters. In fact, the work with the California — I mentioned, with California on fires, is actually about for fire prevention by looking for the stocks for future fires that they can then do clearing in. And we are also working with our soil water content on giving pre-warnings of potential drought risk. Also you can help through that to provide flooding risk. And so some of these datasets can enable getting ahead.
And as I mentioned, civil governments are spending hundreds of billions of dollars a year with these events. Sadly climate change is causing these extreme weather events to increase. And so that hundreds of billions is only going to go up. And we can help them save billions of dollars getting ahead of that. So, it stands the reason — I mean, the civil governments are taking a while to pick this step up, but it is — the pace is increasing and we’ve had — we’ve got a significant fraction of that pipeline that I mentioned of seven- or eight-figure deals is civil government.
Ashley Fieglein Johnson: The other sector where obviously this data is of interest, especially around soil water content as well as soil temperature, is obviously the insurance sector. And that’s both understanding risk models as well as thinking about preparedness for business continuity and business disruption.
Trevor Walsh: Great. Thank you both for that color on that. Super helpful. Maybe just one more from me. With respect to the Sinergise acquisition closing, appreciate the perspective or the additional detail that the revenues might be coming in from that a little bit later than expected. Can you give us a sense of how customer numbers may or may not be adjusted? And I ask, given the fact that you had some nice acceleration in terms of the customer — new customer adds in the quarter and just curious if that is reflective of the Sinergise acquisition at all or if those numbers are not necessarily included yet and how that might look.
Ashley Fieglein Johnson: None of the metrics that we provided from Q2 include Sinergise revenue or customer accounts. Obviously, Sinergise has a very large number of users on their Sentinel Hub platform in addition to a number of enterprise customers that will be coming over and government customers. So, we’ll be updating those numbers and talking about how we roll those into our metrics at our Analyst Day.
Will Marshall: And let me just broaden it out just a tiny bit to say that we are super excited by the acquisition closing. We really think it meaningfully accelerates our data platform strategy. And to my point about small deals in automation and how that’s one of the components of speeding up time to value for customers and sales cycles, especially, and it’s a way of dealing with smaller deals, enabling our AEs to focus on the big deals, Sinergise really helps with that as well. So it’s a product accelerant and it’s a sales accelerant.
Trevor Walsh: Great. Thank you both for taking my questions.
Will Marshall: No problem.
Ashley Fieglein Johnson: Thank you.
Operator: Thank you for your question. Your next question comes from the line of Jeff Van Rhee with Craig-Hallum. You may proceed.
Jeff Van Rhee: Great, thanks. Thanks for taking my questions, guys. A couple. First just on Sinergise, I think the original number was around $7 million was the expectation. I guess it’s going to be a little bit lower here, maybe a month lower, but what’s the number there now in terms of expectation?
Ashley Fieglein Johnson: Sorry. I would give a range of about $4 million to $6 million for the year — for the remainder of the year, sorry.
