Filed by DHC Acquisition Corp. pursuant to

Rule 425 under the Securities Act of 1933

and deemed filed pursuant to Rule 14a-12

under the Securities Exchange Act of 1934

Subject Company: DHC Acquisition Corp.

Commission File No.: 001-40130

Date: January 23, 2024

Full Transcript of SPACInsider Podcast with Michael Zacharski, CEO of BEN, and Chris Gartner, co-CEO and CFO of DHC Acquisition Corp. (made available to the public on January 22, 2024)

Nick Clayton, SPACInsider: Hello and welcome to another SPACInsider podcast, where we bring an independent eye in interviewing the targets of SPAC transactions and their SPAC partners.

AI was one of the big themes for SPACs in 2023. Now in 2024, investor appetite and the market opportunity around AI don’t appear to be going anywhere.

I’m Nick Clayton, and this week my colleague Marlena Haddad and I speak with Michael Zacharski, CEO of BEN, and Chris Gartner, co-CEO and CFO of DHC Acquisition Corp. The two announced a $358 million combination in September.

Michael explains how BEN has built an AI customer engagement tool focused on the auto sales and healthcare spaces, and why those sectors were particularly ripe for disruption. While Chris describes DHC’s process in pulling together a PIPE with strategic investment in a difficult market, and how the SPAC is further supporting the transaction through to close. Both also touch on why they welcome increased scrutiny towards how companies going public describe their AI technologies, or lack thereof. Take a listen.

So AI is having a bit of a moment in terms of buzzy public perceptions, but both some positive and negative headlines out there. But just given how much conversation there has been in 2023 about AI, do you feel like it’s been a net benefit to BEN?

Michael Zacharski, BEN: I would say, for sure. Good to be in a market that has a lot of excitement. I think from the standpoint of BEN and how we are designing our AI assistants, it’s mostly a net positive. We have a good sense of strategy and a product that’s designed around safety and making sure we’re building solutions that work for businesses.

Really, all the conversations around regulation, all the conversations about consumer data privacy, really play well with our strategy and where we sit inside of the AI spectrum.

And so for us, a lot of the chatter is actually very positive, because it allows us to really talk about our strengths and how we designed our solutions to be complementary with how we believe businesses want to and need to leverage these technologies in a safe and also a practical way.

Nick Clayton: Great. And for Chris, I’m really interested in your process as well. It seems like DHC has been following a lot of different trends, and there’s been a lot of changes over the course of the years you’ve been publicly searching. And so just how did you kind of come around to BEN? And what really caught your attention here?

Chris Gartner, DHC Acquisition Corp: I think as you mentioned, AI is obviously in the news right now. And while the technology itself has been around for 50 plus years, we’re finally at the point where the underlying infrastructure, hardware, all the pieces are coming together where you can have real solutions that can be deployed.


And so as we were looking for targets, the most important thing for us has always been the people. And we’ve known a few of the people, the founders of BEN for many years. And when they pulled together the rest of their team, they pulled together their IP, they pulled together all the pieces, we felt that this was the right partner for us. And number one, Michael leading the charge, we felt that this is somebody who can actually deliver the vision that I think most people have for AI, in a very positive way.

Marlena Haddad, SPACInsider: So what people probably see when interacting with your software are the avatars engaging with them. But can you walk us through all the things going on behind that avatar? What really makes it tick?

Michael Zacharski: Yeah, absolutely. So I think a lot of the big AI companies out there have done a really good job of convincing the market that it’s a one size solution and there’s only one way to do AI. That is not the case. You don’t need an oversized tool to do the job that you need to do.

And so really behind the scenes, where we’re focused on is the consumer interface. So it’s the feeling of creating a human-like experience. So consumers feel the benefits of a empathetic, positive conversation, being able to control that timetable and ask really deep and good questions and get rich meaningful answers, as well as complete a task.

So as we move from the consumer interface, the man-machine interface, which is where we are very focused with our AI assistants, referred to as avatars, the backend becomes really important. So we use the layered approach to access the right information and provide a accurate and complete answer. So thinking backwards, we retrieve data, utilizing a different set of techniques, methodologies, like a RAG model. We may run that through a neural network to get to precision.

And then we will use a language model, but we’re using the language models in a way that maximizes their benefits. So how do you then take that answer? And again, the information that we’re retrieving is all provided to us by our customers.

So when you think about what is different with our solution, it’s where we get the data that the AI assistant is pulling information from, from the customer. So customers have the assurance of knowing what information the AI assistant is going to provide. And secondarily, we’re making sure that the language model is providing the benefit of converting that into speech, making it part of the question, part of natural conversation. We’re not using it to do the full job.

And so that gives us a lot of benefits in terms of if we don’t have an answer, we don’t have to make one up. We don’t have to hallucinate an answer, we just say, “We don’t have an answer to that. We’re here to talk about this topic.”

And also from a compute standpoint, it’s much more efficient to operate at scale a solution that utilizes the right size of hardware infrastructure, to both meet the demand of concurrency, to meet the demand of cost management, but also provide a very human-like experience.

So on the backend, it’s not just one system, it’s a collection of systems optimized to do the job at hand, and provide that accurate answer, helpful information, wrapped in a very human-like natural conversation, but also from the business side, making sure the economics are there.

Marlena Haddad: Got it. And your first deployments have been to the automotive sales and healthcare spaces. So what prompted you to look for work in those sectors first?

Michael Zacharski: Yeah, absolutely. Both of those industries have a lot of similarity, believe it or not, in terms of the types of solutions that we’re bringing to market. The other area is they’re both industries that have a labor shortage and challenges with getting high quality workforce deployed, and areas where customers need time. It’s all about providing the customer the time to ask the right questions, to make sure they have time to process the information they’re getting.

And so we found both of those industries as both similar. We found them both as industries that are primed for seeking the maximum benefit from the technologies. And also we see them as great gateways into other verticals as we think about our long-term growth. So both plenty of opportunity in those verticals, but also some challenges.


And so by proving our chops in healthcare, I think it gives us a good position to then think about other verticals as we think about the business and the outer bounds.

Chris Gartner: I think both these industries are being disrupted, they are changing, and very open to AI. So in both cases, as Michael mentioned, they are welcoming the solution that BEN has, as they know that the industry is going to change and it’s either going to change with them or without them. And so deploying the company’s technology, they feel as though at least they’re very well-equipped to not only meet the challenges ahead, but also be a pioneer.

Marlena Haddad: Right. And so BEN has been fine-tuning this technology for the last five years, which must have been an interesting time as you were looking at potential applications. How did the pandemic impact the company’s thinking about opportunities and approaches for this technology?

Michael Zacharski: Well, I think we learned a few things during the pandemic. I’ll start with one that I think we can all relate to, is that I think we learned that we as humans want to go places and we want to see things and do things, rather than be cooped up at home.

And one of the interesting dimensions of our technology is although we can meet the consumer on the web, we also have solutions that are deployed in the real world, in the retail location or in the hospital, where people can actually interact with life-size AI assistants and have a conversation and get the benefit of information, get the benefit of customer service, get the benefit of purchasing something, get the benefit of learning something, in the real world.

So I think we learned people want to be in the real world, people want to go places, people want to see things. We need to make sure the technology meets the consumer where the consumer wants to go and needs to go.

Secondarily, I think people got used to utilizing these technologies in a different way. So on the healthcare side, symptom checkers and the idea of doing virtual appointments and so forth with all the Covid testing, I think really validated to the market that these solutions provide real benefits, and also are something that people are learning how to use and are really primed to leaning into these technologies. And you see it more in healthcare as other industries are bringing virtual appointments to light, and there’s just a big movement on the healthcare side to really meet the consumer where they are and provide a digital solution as a first way of entry to meet your doctor, see the nurse, go to the pharmacy, et cetera.

So I think it was very validating and enlightening to see both that people want to use the technology, and we also want to go places, see things, rather than sit at home with a VR headset on all day.

Nick Clayton: Great. And your presentation notes that much of your business is made up of six-figure enterprise contracts. So how does your pricing work? And how much are you able to layer on different services within each of those relationships?

Michael Zacharski: Yeah. So our platform is designed to stand up and provide the AI assistants to our customers relatively quickly. When you think about that, each business, each customer wants to have a sense of their own branding, their own dimensionality, their own way of doing things. And so we’ve designed our platform to be able to be configured to meet both the physicality of what it looks like, what it sounds like, how it moves, how it interacts with the consumer. But also what the conversation should be like and how you want to guide the consumer through, whether it’s a purchase, whether it’s education, whether it’s customer service, what is the flavor of that experience.

And so we’ve designed the platform to make it easy to configure for each of those dimensions. Make each business have their own AI, as opposed to have a one-size-fits-all tool. But again, to do that at scale, you need to make sure you have a foundational platform that allows for that.

Nick Clayton: Great. And BEN has also tacked on a lot of capabilities that make up this suite through acquisition. So did the company go about it that way as sort of a speed-to-market approach, or would there have normally been some impediments to developing some of this stuff organically without holding the patents? And so what was the IP strategy there?


Michael Zacharski: Yeah, it was both to grab great IP, as well as to maximize on some of the relationships with the universities. So we have a collaboration with Korea University. Really excited about the work that we’re able to fund there, as well as the IP that comes out of it. It’s certainly helped accelerate our flywheel and provide state-of-the-art solution.

And we also wanted to make sure that what we bring to market is best of breed technologically. And so the places where we found that best of breed technology was with one of the acquired companies.

And that plus our foundational patent portfolio around different signal mixing, signal processing, really gave us a strong moat in terms of making sure that what we’re building and the solutions we’re providing to the market are both practical, they’re commercial, but also making sure we have a strong moat protecting our IP as we go to market.

Marlena Haddad: Got it. So just going off of that, what made you decide that now was a good time to go public? And why through a SPAC?

Michael Zacharski: Yeah, absolutely. I think first and foremost, it’s the DHCA team. For myself, I’ve known of Chris for a long time and been very impressed with his work, as well as the team behind DHCA. So not only very accomplished business people, all very well-connected on government and military side, and they bring a lot of that team vision and collaboration to all their projects. We’ve seen it here. So I would say first of all, it’s the opportunity to work with DHCA and then the team there is definitely on the list.

We also see a big opportunity in allowing investors to participate in AI. There are not a lot of choices out there today, a very limited number. And so we see that as a strength of giving investors the opportunity to participate in these technologies now, while it’s still early, and to have the benefit of making those investments as both the market moves forward and we move forward in our business.

Also, obviously opportunity to capitalize the business. So that’s definitely on the list. And we also see it as a leg of defense around our patent portfolio, to ensure that folks know who we are and that we have real tech where it’s defensible, and really show the market what we’re able to do through all those different ways.

So we think it’s a great moment for us to do this now, and definitely the right team to take us through the process.

Nick Clayton: Great. And as you know Chris, not all SPAC deals are the same despite how the financial press may talk about them sometimes. But here at the SPACInsider podcast, we always like to get into some of those details in terms of how the SPAC sponsor is supporting the deal.

And with this one, starting with the PIPE, how did you manage to get some strategic capital involved in that? And what was the process like? Because we know that the PIPE market’s been very tight this year.

Chris Gartner: It certainly has. And I think one of the issues with the SPAC deals is not the instrument, it’s the target companies themselves. The vehicle, again, being a banker for 30 years, the vehicle I think works. The question is what’s the underlying asset?

And so in the case of BEN, he was able to attract capital because of what the company does and the value prop. It was very clear, and look, I don’t want to overstate the company’s position, but this product sells itself with regards to the value that it can bring the end customers.

And so when the strategic saw the product demo, they’re in a space, in the auto space, that’s being disrupted. We all know what Tesla is doing, but aside from that, the whole dealership network needs to respond to, as Michael mentioned, the labor shortage, the way that vehicles are being priced, the dealers, the OEMs trying to do more direct sales. This is a market segment that’s going to change.

And when they saw the leverage that BEN could bring to their own business, and AFG felt that they understood, that customer being in that business for 25 plus years, how it could revolutionize the many different parts of the interaction with the customer as well as the auto dealerships operations, they said we have to be part of this, because if we’re not, the industry’s going to pass us by.


So I think it was one of those moments where the light bulb went off two minutes after the demo started. I get it. I need to be part of this. And I don’t just want to be a customer, I want to be a real partner. And that conversation, no conversation is ever easy in terms of PIPE discussions, but that one flowed very nicely.

Right now, I think the challenge for us is focus. We have to make sure we’re focused on the right verticals. We have to make sure that we’re not being pulled in too many directions. Because as I mentioned, every boardroom, every company is talking about AI. They all want to be part of it. When they see the company’s demos, they say, “Wow, this is a solution we need to deploy.”

So we have to make sure that we’re picking partners, both for the PIPE. We don’t want to go out and do broad sweep of the market for a PIPE. We want to pick people who are truly aligned with us in terms of delivering the solution to customers. And so far, that’s where we’ve achieved our greatest success.

Nick Clayton: Great. And going a little bit further, DHC is further supporting the deal by making some sponsor shares available to incentivize lower redemptions. We’ve seen SPACs approach that particular issue this year in a number of different ways.

I’m curious about your thinking of it and why did you feel like that was an important step in terms of the structure and the end game for going to close?

Chris Gartner: Well, I think it’s important to obviously support the stock and support the trust capital, but also spread the shareholder base with people that we have relationships with.

This is something that we are committed to working with BEN and committed to the deal. And so for us, it’s really about, as opposed to maximizing a single transaction, we want to maximize whatever works for the company and the shareholders going forward. And so if we spend sponsor capital to do that, we’re totally aligned with the people who are willing to support the company going forward.

Nick Clayton: Great. And I’m also interested in your valuation process, just because your presentation notes that you factored in several different cohorts of comparable companies as a part of the analysis. So how did you go about that and how did you sort of weigh the field a little bit given some of the unique tools that BEN has?

Chris Gartner: First of all, we looked at a number of things. Probably the first place we started was the IP. And we got very comfortable, this is going back quite some time, we got very comfortable with the intellectual property that the company had, its process for developing that IP, as well as the ecosystem that was partaking in that IP. So we felt that there’s a fundamental value to that IP. And initially we thought, you know what? This could be a great licensing company. But very early on we felt that was the baseline.

But then very early on, we also realized, wow, this is a team that can really, not only license, but also can operate and capture a lot of that value themselves. So we had the second leg of the stool now being pulled, and that’s looking at what the opportunity was with a team that can actually execute.

So we developed some internal models in terms of the opportunity. Their automotive partnership, they represent roughly 5% of automobile dealerships, so it doesn’t take much to get comfortable with a business model that is able to initially go after that largest segment of dealerships.

The third leg of the stool was looking at comparables. And as Michael said, there’s not a lot of opportunities for investors to really directly invest in an AI company at this scale. It’s going to be difficult to get a 10X off of some of these companies- even the ones that are publicly traded. If you look at the companies that have meaningful AI capabilities, it still only represents a portion of their business. And in addition, getting returns of that scale will be difficult, simply because of where those companies are today in terms of size.


So it was difficult for us to get pure set comparables. But what we did do is we looked at like companies with regards to the opportunity, rapidly growing markets, disruptive technologies, innovative technologies, and created a basket that we felt this was a very fair entry point for ourselves, as well as for the public markets.

Marlena Haddad: And at what point do you think you will look at diversifying into more client sectors, given the big market that you expect to be out there?

Michael Zacharski: Yeah, I think we’re certainly open to it. But to Chris’s point, focus is incredibly important in any business, and especially in a market where there’s so much excitement and so much opportunity, and AI is top of the list in every boardroom globally. We want to make sure that we do the job well and we are incredibly focused on the markets we’re entering, on automotive, as well as healthcare.

And so depending upon the right opportunity, depending upon use cases, that we can be successful in quickly leveraging what we’ve developed for the healthcare and automotive sectors, are likely going to be good indicators.

I would say that we also chose the automotive and healthcare verticals because they’re good gateway verticals into other markets, other verticals that we may want to pursue, both from a technological complexity standpoint in terms of healthcare and making sure that you’re meeting HIPAA and other consumer data requirements, and automotive because of the, call it retail appeal. And so I think through those we demonstrate all the capabilities any other vertical, let it be financial services, let it be retail, pure play retail, would looking for.

So they’re both great verticals from the opportunity size, they’re great verticals from the demonstration of the technological prowess need to be successful in other verticals. And I think that they set us up really, really well long term to expand our horizons as we look at next opportunities.

Chris Gartner: We have seen the discipline that he’s had to have in terms of addressing this market. Every single company that has some sort of customer interaction is a potential customer. So we’ve already been approached by other sectors in the financial industry, hospitality, restaurant. There are a lot of opportunities for us to go after, which I think are all very large markets. But right now we’ve got to get, as the company’s identified, we have to get the ones right that we’re going after, and they’re doing a good job of that.

But the least of my concerns is opportunities. The greatest of my concerns is distraction because of those opportunities.

Nick Clayton: Well, and I guess on the subject of distractions, I just felt like I had to ask while I had you guys here. I’m not sure if you saw the SEC chair, Gary Gensler, recently made comments that the SEC would be looking at cracking down on public companies, quote unquote, AI washing, or exaggerating to the extent to which AI is behind some of their tools.

And I was just interested to get your take on that. Is that sort of a concern within the industry? And it seems like there are certain firms out there that have started maybe pulling back on some of the language they use to describe themselves recently. Just sort of what are your thoughts? How are you thinking about it on your end?

Michael Zacharski: Yeah, I think it’s an important point. One of the things that we were discussing even in the last few days is the fact that every company is throwing in the AI factor. And maybe they’re doing some machine learning, maybe they’re doing some regression analysis. It’s easy to AI wash everything.

Again, for us, this is a great moment because technology’s out there, patents are out there. We’re very comfortable with the years of work and dedication that our team has had developing tools specifically in AI, and we are an AI first company.

So again, all the noise I think really plays to our strength just because of how strong our foundational technology is, as well as our foundational IP. So for us, if the question is really what is AI about your business? The answer is the whole business.


Chris Gartner: I think we actually really welcome that level of scrutiny because it’s incredibly frustrating to sit and listen to the noise that’s being generated in AI. You probably don’t remember the dot-com craze, but back then every company would simply slap dot-com at the end of their name and claim that they were an internet company. And we started seeing that same playbook. People are faking it until they hope they can make it. And unfortunately, I’m seeing they’re doing everybody to service by doing that.

So we welcome that level of scrutiny and hopefully it’ll lessen some of the noise, because then the companies that are actually developing fundamental IP and products, as is BEN, we think it’ll be much clearer to the market to understand.

Marlena Haddad: Definitely. But in general, what is the most exciting thing that you’re looking forward to in advancing this technology?

Michael Zacharski: I’ll answer that question, but I also want to build on what Chris said. I think the other difference is is consumers can actually experience our technology. I think that’s also a big difference. So while many companies can say they do AI, as an individual user, you’re not going to know the difference. You’re not going to see or be able to interact with the technology in any meaningful way.

And because we are in that front, we’re the front face, we’re the consumer interface, people have an opportunity to actually interact with the technology and experience it in their day-to-day life. And I think that’s another component of getting back to the AI washing conversation of how we welcome it and how we’re different.

What excites me most is that same premise, is the ability to allow people to experience the technology in a way that helps them in their everyday life. That helps them with their experience when they’re going to the pharmacy and they may have questions about a particular medication. It helps them if they’re having a procedure done or your loved one’s having a procedure done, and you can have a conversation with an AI assistant that’s knowledgeable about the procedure or your condition and all those things. And you have the right amount of time to actually have an in-depth conversation, versus in the moment, when you have that small window to talk to a professional.

Same thing in the automotive industry. Providing people time to go to the dealership and interact with this technology and answer all your questions fulsomely, and provide you with an experience that’s on your terms, I think is really, really exciting.

And I think it’s really unique to be in a position where not only are we developing leading technology, not only are we doing something really cool, but it’s also applying it in a way that’s helpful and beneficial to society, and something that people will be able to experience in their everyday lives.

Chris Gartner:

If I can add to that, because Michael referred to it, but I would like to just expand a little bit on the personal situation. So several months ago, a number of months ago, we had a family member who required emergency surgery. And got them to the hospital, a very lengthy operation. As you know, these situations are chaotic. And you’re trying to get time with the physician’s assistant, you’re trying to get time with the surgeons, there’s multiple teams involved.

And you can sit in front of a computer and try to Google, and unfortunately Google comes up with trying to sell you sneakers, doesn’t really understand the word, and starts sending you down some very depressing ratholes, aside from the total waste of time.

Fortunately, we had a demo that I had been given by the BEN team, that had the Johns Hopkins Medical Library on it. And so we gathered with my family and we started asking questions. And they were the same questions we were asking the doctors when we had the brief time with them, and the answers were identical. And in a couple of cases when we were talking to the head nurse, things that they didn’t know, we could ask the avatar, and the avatar gave us the answer before we got the confirming answer from the doctor.


So we probably spent I don’t know how many hours talking to the avatar, getting answers about what was happening, what we needed to do, what all the different complications, recovery, all of that. And I can tell you it made a very difficult situation, less stressful.

If you ask about working with companies that can have huge public positive impact, I lived it firsthand, as did my family. And as I said, putting a tool like that in the hands of end users I think will dramatically improve the healthcare experience ultimately, and when it gets widely deployed, I think it’ll help overall level of care pretty dramatically as well.

You give so much leverage to the doctors, the PAs, the nurses, that they no longer have to chase down answers or to spend time with people who have endless questions, and they can get on the path of doing things that only they can do as humans in terms of actual treatment and care.


About BEN

BEN (Brand Engagement Network) is a leading provider of conversational AI technology and human-like AI avatars headquartered in Jackson, WY. BEN delivers highly personalized, multi-modal (text, voice, and vision) AI engagement, with a focus on industries where there is a massive workforce gap and an opportunity to transform how consumers engage with networks, providers, and brands. The backbone of BEN’s success is a rich portfolio of conversational AI applications that drive better customer experience, increased automation and operational efficiencies. Powered by years of research and development from leading experts in AI and advanced security methodologies, BEN seeks to partner with companies with complementary capabilities and networks to enable meaningful business outcomes.

Additional information about BEN can be found here: https://beninc.ai/

Media:

Dan Brennan, ICR

dan.brennan@icrinc.com

Important Information About the Business Combination and Where to Find It

In connection with the BEN’s announcement of its intent to go public via a merger with DHC Acquisition Corp. (“DHC”) (the “Business Combination”), DHC intends to file a registration statement on Form S-4 (the “Form S-4”) with the SEC, which will serve as a preliminary proxy statement of DHC . DHC will mail a definitive proxy statement and other relevant documents to its shareholders. DHC’s shareholders and other interested persons are advised to read, when available, the preliminary proxy statement and any amendments thereto and the definitive proxy statement and documents incorporated by reference therein filed in connection with the Business Combination, as these materials will contain important information about DHC, BEN and the Business Combination. When available, the definitive proxy statement and other relevant materials for the Business Combination will be mailed to shareholders of DHC as of a record date to be established for voting on the Business Combination. INVESTORS ARE URGED TO READ THE DEFINITIVE PROXY STATEMENT AND OTHER RELEVANT MATERIALS CAREFULLY AND IN THEIR ENTIRETY WHEN THEY BECOME AVAILABLE BECAUSE THEY WILL CONTAIN IMPORTANT INFORMATION ABOUT DHC, BEN AND THE BUSINESS COMBINATION. Shareholders will also be able to obtain copies of the preliminary proxy statement, the definitive proxy statement and other documents filed with the SEC that will be incorporated by reference therein, without charge, once available, at the SEC’s website at www.sec.gov, or by directing a request to: DHC Acquisition Corp., 1900 West Kirkwood Blvd, Suite 1400B, Southlake, TX 76092 or by emailing chris@integrity.partners.

Participants in the Solicitation

DHC, BEN and certain of their directors and executive officers may be deemed participants in the solicitation of proxies from DHC’s shareholders with respect to the Business Combination. A list of the names of those directors and executive officers and a description of their interests in the Business Combination will be set forth in the Form S-4. Certain information regarding the directors and executive officers of DHC is contained in its Annual Report on Form 10-K for the fiscal year ended December 31, 2022. These documents can be obtained free of charge from the sources indicated above.


Forward-Looking Statements

This communication contains “forward-looking statements” within the meaning of Section 27A of the Securities Act of 1933 and Section 21E of the Securities Exchange Act of 1934 that are not historical facts, and involve risks and uncertainties that could cause actual results of DHC and BEN to differ materially from those expected and projected. These forward-looking statements can be identified by the use of forward-looking terminology, including the words “believes,” “estimates,” “anticipates,” “expects,” “intends,” “plans,” “may,” “will,” “potential,” “projects,” “predicts,” “continue,” or “should,” or, in each case, their negative or other variations or comparable terminology. These forward-looking statements include, without limitation, statements regarding DHC’s ability to enter into definitive agreements or consummate a transaction with BEN and the expected timing of completion of the Business Combination.

These forward-looking statements involve significant risks and uncertainties that could cause the actual results to differ materially from the expected results. Most of these factors are outside DHC’s control and are difficult to predict. Factors that may cause such differences include, but are not limited to: the inability of the Parties to successfully or timely consummate the Business Combination; the risk that the Business Combination may not be completed by DHC’s business combination deadline and the potential failure to obtain an extension of the Business Combination deadline by DHC; failure to realize the anticipated benefits of the Business Combination; risks relating to the uncertainty of the projected financial information with respect to BEN; the occurrence of any event, change or other circumstance that could give rise to the termination of the definitive transaction agreement; BEN’s history of operating losses; BEN’s need for additional capital to support its present business plan and anticipated growth; technological changes in BEN’s market; the value and enforceability of BEN’s intellectual property protections; BEN’s ability to protect its intellectual property; BEN’s material weaknesses in financial reporting; and BEN’s ability to navigate complex regulatory requirements; the ability to maintain the listing of DHC’s securities on a national securities exchange; the ability to implement business plans, forecasts, and other expectations after the completion of the Business Combination; the effects of competition on BEN’s business; the risks of operating and effectively managing growth in evolving and uncertain macroeconomic conditions, such as high inflation and recessionary environments; and continuing risks relating to the COVID 19 pandemic. The foregoing list of factors is not exhaustive.

DHC and BEN caution that the foregoing list of factors is not exclusive. DHC and BEN caution readers not to place undue reliance upon any forward-looking statements, which speak only as of the date made. None of BEN nor DHC undertakes nor accepts any obligation or undertaking to release publicly any updates or revisions to any forward-looking statements to reflect any change in its expectations or any change in events, conditions or circumstances on which any such statement is based. Further information about factors that could materially affect DHC, including its results of operations and financial condition, is set forth under “Risk Factors” in Part I, Item 1A of DHC’s Annual Report on Form 10-K for the fiscal year ended December 31, 2022.

No Offer or Solicitation

This communication does not constitute an offer to sell or the solicitation of an offer to buy any securities of BEN or DHC or a solicitation of any vote or approval. No offer of securities shall be made except by means of a prospectus meeting the requirements of Section 10 of the Securities Act of 1933, as amended.


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