How Vertex plans integration during diligence, and where AI helps
Dan Furman, integration program manager at the Vertex Companies, explains how his team frames due diligence around an integration plan agreed with the seller before close, and where AI fits: target research, tighter request lists, discrepancy checks and contract review. Worth watching for his plain rules on keeping judgement human.
- Dan Furman · Integration Program Manager, The Vertex Companies
- DealRoom moderator
- Vertex involves its integration team from the start of a deal, with no formal handoff, so a plan everyone has bought into is ready on day one.
- The team frames diligence questions so they feed an integration plan before closing, and discusses joint opportunities with the seller in parallel.
- Furman says AI helps keep diligence requests concise, avoid asking for the same information twice, and spot discrepancies in what sellers provide.
- He has been impressed by AI contract review, but says you still have to read and understand everything yourself.
- AI recommendations should be treated as validation, with human judgement paramount.
- The biggest mistake he sees corporate development teams make is relying on AI more than on their people.
At the Vertex Companies there is no official handoff point between the deal team and the integration team. Dan Furman, its integration program manager, says the integration team is involved from inception, so that on day one there is a plan everybody has bought into (around 10:43). Diligence is shaped around that. There are questions that just need to be asked, he says, but the team frames its diligence so it lends itself to an integration plan prior to closing.
“There are questions that just need to be asked in diligence, but we really try to frame our diligence so it lends itself to an integration plan prior to closing.”
Dan Furman, Integration Program Manager, The Vertex Companies
Vertex is a professional services firm in expert, forensic, construction project advisory and compliance and regulatory services. Furman joined as a summer intern in 2015 and moved into M&A in 2021, when acquisitive growth took off, to revamp due diligence and set up the integration programme. The corporate development team is led by the chief strategy officer, a Vertex founder, and includes founders and leaders who came in with acquisitions and went through integration themselves. The session is a DealRoom webinar, with a DealRoom moderator.
“Our integration team is involved from inception. So, there's no official handoff point.”
Dan Furman, Integration Program Manager, The Vertex Companies
The seller is part of that plan. In parallel with diligence, Furman says, the team discusses with sellers the opportunities neither side could get alone and how to pursue them. The moderator describes the seller's side: anxiety about when systems change and how the team will be treated. Furman says the idea is to alleviate those concerns so the time goes on how the businesses come together. Developing trusting relationships, he says, is what corp dev people bring to the table that AI really can't replace.
“You're still going to have to read and understand everything. You can't read SparkNotes and feel confident that you know a book well.”
Dan Furman, Integration Program Manager, The Vertex Companies
Before AI, Furman spent far more time prospecting: hours of internet searches, repeat results to sift through, information that was not easy to find. It is now available a lot quicker, he says. On outreach he is more careful. AI can reveal insights worth using, but the message needs to be personalised and sincere, and it needs to sound like you. Company leaders, he expects, are becoming a lot less receptive to outreach that is clearly not prepared carefully.
“Over reliance on AI and less on people. Don't forget how important your team's insights are just based on their own experience in dealing with people.”
Dan Furman, Integration Program Manager, The Vertex Companies
In diligence the gains are practical. The team has always tried to make concise requests and not ask for the same information more than once, and Furman says AI has really helped with this. It also helps identify discrepancies in the information sellers provide, and with analysis and summaries. He says he has been pretty blown away by the contract review capabilities he has seen (around 6:40). Information born out of the M&A process that colleagues elsewhere in the company need is now summarised and shared with them on a continued basis.
None of that changes who decides. Asked where human judgement should override AI, Furman says human judgement is paramount and AI recommendations should be considered as validation: AI helps you make sure you're not missing something, but you make the decisions (around 11:31). He compares it to reading a book. You still have to read and understand everything, because SparkNotes will not make you confident you know a book well. Question the results you're getting, he adds.
On integration itself, Furman describes building a repository of plays from prior integrations that make up the playbook, then considering what is new about the next deal. AI can help there, he says, by weighing historical information in the context of new information, and by taking what was learned in diligence to suggest how to handle it. The human part, the trust built with the seller before closing, is what he wants to stay in control of. Asked for the biggest mistake corp dev teams make with AI right now, Furman answers: over reliance on AI and less on people (around 16:48).
His advice for hesitant teams comes from someone who was one pretty recently. It is not so scary, Furman says. Don't try to use it for everything all at once. Pick small, specific use cases, things you think could be better, and test AI tools on them. Recognise the sensitivity of the information you are dealing with. And treat it like an experiment.
Furman's habit of asking for each piece of information only once is where AI meets the data room: a tighter request list means fewer duplicate uploads and a cleaner Q&A for the seller. Framing those requests around the integration plan also means the room ends up holding what the post-close team needs.
All right, and we are live on our side. Top of the morning everyone. Thank you as always for joining us. As usual, feel free to continue to throw your LinkedIn in the chat, connect with some other practitioners, meet some new folks who are like-minded and doing the same work that you're doing. Also, as you have questions throughout today's session, please feel free to use the Q&A. We will be looking to spend about 5 minutes towards the end of the session to answer those. but really I am excited to be presenting alongside our guest today. So really what we're talking about today is AI and M&A in in practice. And so I'm very happy to be joined by Dan Furman from the Vertex Companies. Now as a quick note, Vertex has built one of the more intentional M&A practices in their spaces. They're integration first, relationship-driven, and AI has become a key part of how they execute Now, without any further ado, I would
love to hand it over to Dan Furman to to introduce himself. >> Hi everybody. So my name is Dan Furman. I'm with the Vertex Companies and I'm the Integration Program Manager. So a little bit about Vertex, Vertex is a professional services firm specializing in expert forensic construction project advisory and can compliance and regulatory services. So what we do is we help our clients remain compliant, manage projects effectively, and resolve disputes. >> And Dan, correct me if I'm wrong, but you began at Vertex as an intern, right? >> That's right. So I joined Vertex while I was an intern, a summer intern, when I was in college in 2015.
I joined the company to help build out a new service area. I worked a bit with each of our service areas since then, and now this is what I do. >> And so tell me at what point did your like focus [snorts] actually shift towards M&A? >> My focus shifted towards M&A in 2021, when our acquisitive growth really began to take off. So at the time I was given the opportunity to work with our M&A team to, you know, to to revamp our due diligence process a little bit and establish our integration program. And now we have a dedicated corporate development team with an integration forward approach. >> Incredible. So you've you've really been there through the full ride. Now, Dan, could you without giving anything too proprietary, could you give us a quick snapshot of Vertex's M&A program and what makes your approach different from most teams?
>> Sure. Well, I think one thing that makes our approach interesting is that our team is led by our chief strategy officer who's a founder with Vertex. We also have another founder on the team, and we have founders and leaders who have come with acquisitions. And then of course there's me and another teammate who comes from the operations side. >> And given that, you know, folks have come in via acquisitions and coming up through the company, I would imagine that your team really embodies Vertex's culture. >> We do, but but also what makes the team unique is we've got these leaders and founders who have come with acquisitions, and they've been through integrations with us. So it brings a real unique perspective to the team, I think.
And you know, on top of that, too, you know, we talk about our integration focus. I think one of the things that makes our team interesting is that this dedication to integration is also fully embraced by our by our PE partner. >> Which is one thing that we've discussed in the past and I always thought it was incredible, but not only that, but we've talked about how your team's approach to due diligence isn't just about getting the deal done. Tell me more about that. >> Yep. So, you know, there are questions that just need to be asked in in diligence, but we really try to frame our diligence so it lends itself to an integration plan prior to closing, right? And in in in parallel with that diligence, we're also actively discussing with sellers the opportunities that we think neither one of us could get alone and how we're going to pursue them.
>> So, in short, would you say that the time to plan for opportunities and align on how the businesses will come together isn't post-close, it's actually pre-close. >> I completely agree, Dave. >> Incredible. Now, Dan, tell me a little bit before AI entered the picture, which aspects of your process could have been improved? >> So, I'll tell you right off the bat that I used to spend a lot more time prospecting and researching targets. just hours of internet searches, repeat results to sift through, and just a lot of information that was not easy to find. it's now more available a lot quicker. >> A lot quicker. And and how about with diligence?
>> And with diligence, you know, I would say we always strive to make concise requests and not to ask for the same information more than once. And you know, in I'll be succinct and just say that AI has really helped us with this. >> Incredible. Now, I think the really the big question, could you walk us through how your team is actually using AI today from like pipeline early stages all the way throughout diligence? >> For sure. So, for prospecting, it you know, we've discussed how it helps us identify quality targets in a fraction of the time. It can also help refine outreach, but what I'll say about that is that your outreach in the end needs to be personalized and it needs to be sincere.
>> [snorts] >> It especially with, you know, the age of AI and automation and volume. I I imagine company leaders are becoming a lot less receptive to to outreach that is clearly not prepared carefully. >> Very desensitized to it. I mean they're getting bombarded. and what I'll say is AI can really help reveal some valuable insights that you can consider in your outreach, but in the end it needs to sound like you and it needs to convey genuine interest. >> And so the focus is really about bringing value to your messaging. That's that's incredible. Now, how about with due diligence? How are you using AI there? >> So with diligence, I mean these tools like like I mentioned before can help refine an outreach. So we we like to keep them succinct. We want to make sure we're not missing anything either. Of course, it helps with it identify discrepancies in information that's provided. it's very helpful in performing analysis.
the summaries are very helpful and and I'll say too that I've been pretty blown away by the contract review capabilities that I've seen. >> And out of curiosity, have you found like are there other ways the company can benefit from like the way your corp dev team uses AI? >> Yeah, and you know, without being too specific here, I'll say that there's information born out of the M&A process that other teammates need, you know, outside of where we maintain this information. So we've actually worked with the deal room AI features to summarize this information, highlight what's needed, and share it with those who need it on a continued basis. >> And so really here we have a a use case that goes beyond M&A, but that actually came from your M&A workflows. That's super interesting.
>> Yeah, it's great. >> Awesome. Awesome. Now, when AI takes manual work off your plate, what do you actually do with the time? this is a a hot topic question I've heard from a lot a lot >> Yep, so outside of deals that are going on, I mean it just gives us more time to identify quality targets and perform thoughtful outreach. And then in the time leading up to closing on deals, we're planning integrations and we're talking about how we're going to pursue opportunities together. >> And so listening to you, my takeaway is that efficiency and diligence is actually creating space for conversations that actually move the deal forward. Not only that, but it helps in creating lasting value after the close. You know, sitting with seller pre-close to talk about opportunities, joint goals, and what the future looks like together.
>> Yeah, what what it allows us to do is spend time developing trusting relationships. And that's what we corp dev folks bring to the table that AI really can't replace, you know, developing these trusting relationships. >> Yeah, and if if I were to put myself in the seller's shoes during diligence, I could see myself getting really anxious about like integration, and that could negatively impact the deal, you know, thinking about things like when are we going to move to new systems, how is my team going to be treated? And I can see how it'd be really comforting to proactively have these conversations and like know it would be handled thoughtfully as a seller. >> Yeah, the the idea is to alleviate concerns so we could spend more time talking about how we're going to come together and pursue opportunities.
>> Incredible. And how about for the M&A teams who are in this room who are hesitant about using AI or just getting started? Like what would you tell them? What would your advice be? >> Good question, and I was one pretty recently. So, you know, I'm glad to say like it's not so scary. What you should do is understand it's not going to replace anything, right? And don't try to use it for everything all at once. Pick small, specific use cases, things that you think could be better, and test AI tools, right? What I'm going to too is you're still going to have to read and understand everything, right? You can't read SparkNotes and feel confident that you know a book well, right? But these are helpful tools. you know, and and in the end, oh, you know, I'll I'll also say recognize the sensitivity of the information that you're dealing with.
but have fun treating this like an experiment. This is going to go a lot of different directions, but it's all helpful. >> Now, it it's it's incredibly helpful and I really like your your perspective there at the end. Like, have fun, experiment. you know, there's a lot that you can do out there with AI, but it's always a real like iterative process and understanding where are the key areas that can help you improve and like really developing that. >> That's right. >> Awesome. Well, with that, that was a a quick little session on some practical use cases, how folks are actually using AI in M&A, and most importantly, what they're doing with the time.
with that, we actually have a couple of extra minutes for questions, and I suspected so. Would love to hear what what's on top of mind for folks. >> [snorts] >> All right. question from David, at what point in the deal process do you formally start to engage the integration team, and how do you approach integration planning at that point in time? interesting question for you, Dan. >> That's That's a great question. Our integration team is involved from inception. So, there's no official handoff point. All of our team members are involved in every aspect, and that way, we're all part of the planning. And like I said earlier, we want to be at a point on day one where we have a plan that everybody's bought into that we can move forward with.
>> [snorts] >> And I I think the the real interesting part there is not only you and your team are bought into the plan, but the seller is as well, going back to that previous point. >> Absolutely. >> Awesome. Let's see what else we have for questions. Roman, where should human judgment override AI recommendations in cyber M&A decisions? >> I would say human judgment is paramount, and I would say that AI recommendations should be considered as validation. >> Yeah. >> If that makes sense. That's the way I think of it, you know, we have a team with people that specialize in making these decisions. AI brings insights, it helps you make sure you're not missing something, but in the end, you're the one making the decisions.
>> And for folks who've spoken to me before, they'll know that I I 100% agree with you. AI is really It's an augmentation, it's meant to help people move faster so that you can spend your time on some of the lower smaller like value-added activities, but it should never really be a replacement. So, I think a recommendation is really exactly that, it's a recommendation. >> That's it. >> Awesome. Let's see what else we have. >> [sighs and gasps] >> For you, and this is a great question. when did AI stop being a let's experiment project for your team, and when did it actually begin being part of how you actually work?
>> Dave, I like what you said before about it being iterative, because, you know, you never want to let go of the reins on anything. but keep using it where it seems to be helpful. Right? So, there's some simple things, like when you're just doing a search, right? You know, types of information you want to find out about targets. you know, I I mentioned that I'm able to find information quicker, I'm going to continue doing that. and that's kind of my my attitude towards all this stuff. But in the end, you know, back to that last question, human judgment I think is paramount. >> Yeah, absolutely. and you know, without that that human judgment, like that's when things get overboard really quickly. And so I again, like that's the most paramount piece is experiment, be super additive, start small, but then I think folks would be surprised by how quickly like a small experiment can actually be something that saves them.
Even if it's 10 minutes a day, you know, that's almost an extra hour out of the week. I wish I had an extra hour out of the week. >> Yeah, no, it's never going to replace your analysis, it's not going to replace anything, it's going to augment, like you said, Dave. Let it keep augmenting, but question the results you're getting. >> Absolutely. Absolutely. Love that question. let's see what else we have. Mike, I'm curious how you leverage AI in the integration process. Specifically, when it comes to better understanding the target company, i.e., key customers, key employees, and relationships. >> Okay, so my first thought is that you know, you end up building a repository of plays, right? They make up your playbook and how you've treated all prior integrations and you consider what's, you know, new about this one and how you're going to do it differently.
I think AI can help with that. I would say that yeah, so so it considers historical information in the context of new information. And I think that that's where it can help you plan things effectively. But again, you got to use your judgment. >> Yeah, the I think the judgment is absolutely the the key point here and I think this is an extra interesting with the approach that you and the team take since you know, you're so involved in the the early stages when you're planning integration. I think that really helps without like losing that context layer because the folks who are going to be ultimately using this information once the deal is closed is actually writing side by side the actual diligence process itself and so I think that lends itself really well to this question. but it's it's not easy. I I think the question is like hey, we know how you can leverage AI and what for but you know, how do you actually make it useful, save you time that so you can move on to the next big thing.
>> And then back to what we were saying before that we we build trust with sellers in the time leading up to closing. We're actively discussing what's important about their business and how we're going to come together in an effective way. So again, AI could take that past information, the new information that you produced in diligence and make some good recommendations on how you might want to handle this but in the end, there's that human aspect that you want to be in control of. >> Yeah, and it's it's interesting. It for you like AI allows you to be more intentional and build more of those human connections which is almost ironic in its own way. >> [snorts] >> thank you for the question Mike. I think we have a couple more we can do. This one more.
Another good question. What is the biggest mistake you see corp dev teams making with AI right now? >> Over reliance on AI and less on people. Don't don't forget how important your team's insights are just based on their own experience in dealing with people. I think we we can't let go of that. >> Absolutely not and if there's one takeaway about Dan and I that folks can take from this it's our stance on AI. It's it's an augmentation that allows you to almost spend more time being human. It's about how you spend that time and how you use the AI but it's absolutely a powerful tool but it could also go haywire real quick.
So I think that's that's awesome. >> Agreed. >> Alrighty, with that I just want to say thank you. Thank you everyone. Really appreciate you joining us this top of the morning early afternoon for you. Hope this made a pretty decent lunch session. >> [snorts] >> Also, one thing I want to mention is if you're using AI in your deal process today we'd love to hear from you. We're running an AI survey right now which you can find in both the comments and it should be in a link right below me. Really again thank you all for for joining us. I hope this was informative and got you you know noodling on one of the ways that you could use M&A in your day-to-day and really get that ball rolling there if you haven't already.
It's definitely a hot topic. And also a giant thank you to Dan. Dan, really appreciate you joining us. I think this was a great session that people can get some great takeaways from. >> Yeah, thanks for having me Dave and the rest of the team. >> Absolutely. Now everyone just sit tight. We are going to have our next session starting shortly with the fantastic Supritha and Ashley from the DealRoom team. All right. Thank you everyone. >> Thank you everybody.
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