EX-99.1

Exhibit 99.1


		Raw Transcript

05-Nov-2018

Altair Engineering Inc. (ALT R)

Acquisition of Datawatch Corporation by Altair Engineering Inc Call


		Total Pages: 14
1-877-FACTSET www.callstreet.com		Copyright ^© 2001-2018 FactSet CallStreet, LLC


Altair Engineering Inc. (ALTR)		Raw Transcript
Acquisition of Datawatch Corporation by Altair Engineering Inc Call		05-Nov-2018

CORPORATE PARTICIPANTS

Howard N. Morof

Chief Financial Officer, Altair Engineering Inc.

OTHER PARTICIPANTS

Richard Davis

Analyst, Canaccord Genuity, Inc.

MANAGEMENT DISCUSSION SECTION

Operator: Good day, ladies and gentlemen and welcome to the Altair Announcement of Acquisition of Datawatch Conference Call. At this time, all participants are in a listen-only mode. Later we’ll conduct a question-and-answer session and instructions will follow at that time. [Operator Instructions] As a reminder, this call is being recorded.

I would now like to introduce your host for today’s conference Howard Morof, Chief Financial Officer. Please go ahead.

Howard N. Morof

Chief Financial Officer, Altair Engineering Inc.

Thank you. Good morning. Welcome and thanks for attending this call regarding Altair and Datawatch. I’m Howard Morof, I’m Chief Financial Officer of Altair. And with me on the call is Jim Scapa, our Founder, Chairman and CEO along with Michael Morrison, President and CEO of Datawatch.

Prior to today’s market opening we issued a press release with details regarding our acquisition of Datawatch, which can be accessed on the Investor Relations section of our website at investor.altair.com.

This call is being recorded and the replay will be available on our IR website following the conclusion of the call. During today’s call we will make statements related to our business that may be considered forward-looking under Federal Securities Laws.

These statements reflect our views only as of today and should not be considered representative of our views as of any subsequent date. We disclaim any obligation to update any forward-looking statements or outlook. These statements are subject to a variety of risks and uncertainties that could cause actual results to differ materially from our expectations. These risks are summarized in the press release that we issued today.

For a further discussion of the material risks and other important factors that could affect our actual results, please refer to those contained in our Quarterly and Annual Reports filed with the SEC, as well as other documents that we may file from time-to-time. During the course of today’s call, we refer to certain non-GAAP financial measures.

Finally at times in our prepared comments or responses to your questions, we may offer metrics that are incremental to our unusual presentation to provide greater – greater insight into the dynamics of our business or our quarterly results for this transaction. Please be advised that we may or may not continue to provide this additional detail in the future.

With that, let me turn the call over to Jim.

James R. Scapa

Chief Executive Officer, Altair Engineering Inc.

Thank you, Howard and thank you all for joining this call on short notice. Today, we announced the acquisition of Datawatch, a publicly traded data preparation, data science and real time, visual analytics company with a long and strong market presence, a well-established best in class products used by customers including 93 of the Fortune 100.

Datawatch is primarily active in the financial services and capital market space. However, it’s technology is highly relevant and applicable to almost any company in vertical market today. Bringing Datawatch into Altair should result in a powerful offering consistent with our vision to transform product design and decision making by applying simulation data science and optimization throughout product life cycles.

We see a convergence of simulation and the application of machine learning technology to live and historical sensor data as essential to creating better products. Marketing them efficiently and optimizing their in-service performance. The data analytics and data science market are evolving rapidly to leverage.

many of the same technologies such as high performance computing and visualization as we have been leveraging simulation for years. Altair will now be able to provide our customers a broad solution offering under a compelling licensing model to meet all of their digitalization needs. Datawatch is by far Altair’s largest acquisition to-date and our first of a publicly traded company. A critical component of Altair success has been our company culture on which we pride ourselves and invest substantial time and resources to ensure it continues.

We believe this has helped us to successfully integrate so many companies until now and that this will allow us to be successful with Datawatch as well. There is currently very little overlap between Altair and Datawatch customers, we see opportunities to disrupt Datawatch’s traditional markets by applying our proven licensing models to promote more usage of Datawatch products, as well as some relevant healthcare products.

In addition we see a strong opportunity to cross-sell Datawatch products into Altair’s primarily manufacturing customer base. We believe we can grow revenues for Datawatch technologies by moving their products in to our HyperWorks units licensing model. Michael Morrison is with us this morning to offer some perspective from the Datawatch organization. It’s been a pleasure to work with Michael and his team throughout the process of getting to know the company and planning for the acquisition. Michael?

Michael Morrison

Chief Executive Officer, Datawatch Corporation

Thanks Jim, and let me emphasize how pleased I am to be with you on this call today. We are very proud of what we’ve built here at Datawatch. Our innovative data analytics platform, the customers we serve and our dedicated

our innovative data and analytics platform, the customers we serve and our dedicated and passionate employees. We’re excited about this opportunity to join forces will Altair and help transform the market while accelerating sales of our Monarch, Panopticon and Angoss platforms. I feel great to be bringing our team into a company with such a strong culture of innovation and I’m confident that we’re going to succeed in building business across combined markets. Jim?

James R. Scapa

Chief Executive Officer, Altair Engineering Inc.

Thank you, Michael. And on behalf of the entire Altair organization we sincerely look forward to great success with the Datawatch team. The acquisition is pending regulatory approval and we anticipate talking more about it after the transaction process is completed.

Now I will turn the call over to Howard for financial details of the planned transaction. After we -- we look forward to answering your questions. Howard?

Howard N. Morof

Chief Financial Officer, Altair Engineering, Inc.

Thanks, Jim and Michael. Starting with the terms of the agreement we have agreed to a purchase price of $13.10 cents per share representing a fully diluted equity value of approximately $176 million. The transaction has been approved by the board of directors of both companies and we expect to complete the cash tender offer and close on the transaction during the fourth quarter subject to customary conditions, regulatory approval and any potential required extensions of the offer.

With respect to the financing for the transaction we expect to use a combination of our cash balance and debt from our newly expanded revolving credit facility. As a reminder, we exited the second quarter with over $199 million in cash and we expect to generate solid cash flow in subsequent quarters.

Terms on the revolving line of credit, our LIBOR plus a range of 125 basis points to 200 basis points depending upon leverages defined in the agreement.

From a financial profile perspective, Datawatch is a publicly traded company with up to date financial information that investors can access. From summary level summary level perspective, Datawatch’s trailing 12 month GAAP revenue ending June 30th, 2018 was reported at $40 million. Their GAAP revenue for the quarter ended June 30th of 2018 was reported at $11.1 million, an increase of 23% over the same quarter in 2017.

We expect the acquisition of Datawatch to have a near-term positive impact on our revenue. We will provide additional views into how we expect Datawatch’s operations to contribute to Altair, when we report our fourth quarter and year end 2018 financial results assuming the transaction has closed as expected.

In summary we are very excited to announce our agreement to acquire Datawatch, which we believe is great news for both companies, our customers, our partner ecosystems and our employees. There is a high level of alignment with this acquisition towards Altair’s vision and we believe a long-term positive financial impact on Altar’s overall results.

With that operator, can we now open up the call to questions.

QUESTION AND ANSWER SECTION

Operator: Thank you. [Operator Instructions] Our first question comes from the line of Sterling Auty with JPMorgan. Your line is now open.




Sterling Auty		Q

Yeah. Thanks. Hi, guys. James can you just talk

Yeah. Thanks. Hi, guys. James can you just talk to us between this acquisition and the last one, how much of this is a competitive answer to what...........00:10:01

Sterling? Hey, Sterling? Operator, can you hear us?

Can you hear me?

Operator: Yes, sir.

Hi. Sorry about that. So how much of this acquisition and the last acquisition is a competitive answer to what Ansys is doing with Discovery Live and how much integration work is going to be necessary to kind of have something that feels comparable in the market?

Okay. So first of all, the Datawatch acquisition has nothing to do with what Ansys is doing relative to Discovery Live. The SIMSOLID acquisition is certainly more relevant to that and it isn’t exactly an ancillary to what they’re doing, but it is very competitive I guess with what they’re doing. So SIMSOLID and Discovery Live are really trying to address the designer and design engineer markets. It’s something we talk about for many, many years being able to have the designers do simulation and certainly, moving simulation in front of design has been almost a passion for Altair for a long time and we do it already with our Inspire solution. The SIMSOLID technology will be integrated inside of SIMSOLID. We’re still going to keep the other simulation technologies that we have in there and there are so many and growing, but SIMSOLID is frankly pretty revolutionary technology.

frankly a pretty revolutionary technology, it’s on the map, it’s completely unpublished and in all sincerity, I myself was just enormously skeptical about it, but we just tested the hell out of it frankly. And it’s quite remarkable and it’s different than Discovery live with some solid you can handle large assemblies. It’s blazing fast, there’s absolutely no mission going on under Discovery live. There’s a mash being created with the box on mesh. This is really – I think a leap in technology and you wouldn’t believe. I think we have and I don’t want to quote numbers because I may get them wrong but there’s probably close to a million views on the video already. And just a huge number of people signing up for the webinars and everybody that spent playing with it is jaws are dropping. We showed it at our conference and some of the reaction was actually fear from analysts who’ve been doing this for a long time. It’s certainly in the same space is what Discovery live. But I think it’s quite a much bigger leap and then what Discovery live is.

All right great and then maybe one follow up here for so then for Datawatch. What is the primary use case that you envision your core customers utilizing the technology for?

Right. So there’s three main technologies that are sort of with the Datawatch solution. But the first is sort of the state of data preparation. Every company has got data all over the place, business data, marketing data,

engine data and often in many different places and many different forms and so the Datawatch foundational technology lets you bring that data in very, very easily. It has a huge number of tools. They’ve been around a really long time I think it’s – it is arguably the best data prep technology on the market many might argue.

And so you basically need that everywhere, across everywhere. The second is Angoss technology which is machine learning environment, it’s an environment to set-up doing machine learning and we think that’s going to be relevant for anybody who is trying to apply machine learning algorithms to whether you’re trying to do predictive analytics for predicting failure or we see actually even applying it to some of the core things that we do, some of the simulation things that we’re doing for crash or optimizing for crash and those sorts of things.

And then the final piece is this real time data streaming and visualization and that’s completely relevant to the IoT data that you’re bringing in of course customers who have streaming data from marketing and other sources as well. It’s very relevant, financial is where they’ve played a lot, but the core technology is that -- there’s really not much like it in the market and we think it’s just going to be huge with all the data coming from IoT.

All right. Great, thank you.

Sure.

Operator: Thank you. Our next question comes from the line of Matt Hedberg with RBC Capital Markets. Your line is now open.

Hey, guys. Good morning. Thanks for taking my questions. I wanted to ask Michael a question about the competitive landscape as well as some of your best partners, it looks like Tablo is a good partner for you, but I’m wondering about the competitive landscape, Alteryx, I guess anything in particular that, that would be helpful?

So, thanks. On the data prep side, Alteryx is the name brand in data prep. There’s a few other smaller companies that are out there, but – and Jim was just talking about on the Angar side, and Panopticon, and on the other real-time visualization side, there really isn’t a comparable product out there. We typically compete against building yourself. And so, when you get into the IoT space and real-time streaming data, and time series data, we feel very – we’re very confident about how we stand.

On the Angar side, and we acquired Angar back in January, a very robust solution that we’ve typically applied in the financial services area, but when you think about it, doing predictive and prescriptive analytics, and whether it’s manufacturing or automotive, or whatnot, being able to take all the data sets that are developed through simulation, and predict what’s going to happen, it’s the space there, the big players are SPSS and SaaS, although that market is being disruptive, the same way that the traditional BI market was disrupted. So where I’d like to think of Angar just sort of the next generation of predictive analytics.

That’s great. So, I’d like to thank Vanguard, sort of the next generation of predictive analytics.

That’s great. And then maybe a quick one for Howard, it looks like about – I think about 60% of Datawatch revenue is recurring. How should we think about transitioning that over to your HyperWorks units, I mean, I know the deal isn’t closed yet, but just any sort of help and sort of thinking about that revenue run rate from a high [indiscernible] perspective will be helpful?

So, obviously what we like to do is take all of our technologies under a big shift to recurring revenue. So as that occurs, there will be some effort and attention that we’re going to have to spend on that conversion, but we believe that on the whole even if there is a little bit of noise in a very short time period around that converting to the recurring revenue model, our HyperWorks units model it actually will drive a lot of utilization and revenue growth as we look outward.

I can add to that just a little bit. I think we anticipate the you won’t see, I mean, this is too forward, but you probably won’t see growth in the first year as we make this transition, you might even see a slight decline in revenue in year one in 2019, because we’re going to be pretty aggressive to try and shift to subscription more from the perpetual model. So, our goal is to bring the recurring revenues up over a period of years to more in line with what Altair does. And there’s a little bit of pain in the beginning, but it builds for a much more robust business and by shifting things to units and floating licenses and things like that it’s very customer-friendly it gives us the ability to bring all of the tools that that Datawatch has assembled it makes all them available to other customers, which I think is going to be interesting. And there are some tools in the Altair solution set which we think are also going to be relevant to their traditional -- to the traditional Datawatch customers as well that will be available. And then, within our market base we think a lot of these tools are going to be very interesting to those folks and we’ll do a lot of cross and up-selling really both directions. But there is a lot of focus on shifting to subscription.

Super helpful. Thanks a lot Jim.

Yeah.

Operator: Thank you. Our next question comes from the line of Richard Davis with Canaccord. Your line is now open.




Richard Davis Analyst, Canaccord Genuity, Inc.		Q

Thanks. So I just want to make sure I understand it, so the Panopticon business is a really good visualization tool. And so then Jim you’re going to keep the other parts of the Datawatch and then so start selling more to like marketing departments competing straight up against Alteryx and Tableau, and TIBCO and those kind of things. I’m just trying to figure out where are you -- so is there going to be incremental investment on those sides to kind of grow that side of the business to sell to customers and people and segments that you haven’t done before? Thanks.

Right. So -- I mean – sorry, we all sound like frogs because it’s pretty early for us here in California, if you are wondering. So the Datawatch customer base especially for Angoss and for Panopticon is capital markets and financial services of course. They actually have a lot of customers that are in many many different domains from health care to manufacturing for sure.

What we’re really relying on is the fact that we already have established business with 6,000 clients and that are HyperWorks units model is allows products in our portfolio to be run by those companies and that’s how we bring any new product that we brought into the portfolio to market.

So what we have to do is we’ll probably develop a team that does if you will hunting in the Altair customer base and the hunting is not to go get a purchase order necessarily but to go find where the user communities are for these technologies and then do training, promote training, promote usage and then partner with the existing account managers of those -- of those accounts to have success there. Is that clear or am I...

Yeah. So you would be hire – so you’d hire, so if I’m a salesman for Altair and I’m selling simulation. We’re going to have like an overlay person come in and try to sell to the marketing department and the customer service department and all of those things, because I probably don’t know those people I would think if I was selling stimulation.

Right.

So I was just want to make that...

With the Datawatch guys doing all those people -- so we’re going to -- we’re going to realign a little bit their sales organization and put together a team that would call on the Altair customers in partnership with those account man and that -- it’s actually what we do with almost every acquisition, we acquire technology for electromagnetics for example for high frequency electromagnetic, the traditional account manager for Altair they

that calls on JLR for example doesn’t actually know those departments. So usually the new company that’s brought into us they have sort of this business overlay people that partner with our account managers, run the accounts to go find those departments and open them up. And don’t get me wrong – it’s lots of hard work, there’s challenges there and there’s some risks too of course. But in general we think it’s something we’ve done over and over again.

Okay. Thank you.

Yeah.

Operator: Thank you. Our next question comes from the line of Bhavan Suri with William Blair. Your line is now open.

Hey guys it’s actually Arjun Bhatia if for Bhavan. Just wanted to clarify real quick on where this exactly fits within your product portfolio and how you anticipate to integrate this. Is this going to be part maybe in the next year or so right after you do your integration do you see this as being part of the HyperWorks offering and solidThinking or is this going to be completely separate?

I see it as part of HyperWorks. So HyperWorks is almost a marketplace, almost every really every application software that we have on the portfolio is available under HyperWorks units and – but not under solidThinking. So it’s not really relevant under solidThinking and we see converting the existing Datawatch customers to the HyperWorks units model where they now can run whichever product they acquired. But also additional products that are in the portfolio will be available to them, as well as some products that that could begin to be interesting to those accounts for example we have some technology for developing Python scripts for example and 00:25:40 to do that or some of the optimization tools. So, that that’s where we see going.

Okay, great. That’s helpful. And then as you look at your – Jim if you look at current customer base, have or your customers using a solution currently for data science and visual analytics or do you anticipate this when you do your cross-promotions, do you anticipate this being more of a greenfield opportunity within your base.

I think it’s both. I think a lot of companies are starting to do data science of course and everybody wants to. And so you know some of the companies that were mentioned earlier whether it’s Altarex or others you know are certainly trying to attack those accounts and all the customers and they’ve had some success. But as I think you guys understand it’s a pretty big market.

Great. Thanks for taking my questions.

Operator: Thank you. Our next question comes from the line of Richard Valera with Needham & Company. Your line is now open.

Thank you. Jim I know it’s early but I’m wondering if you can talk about any of your thoughts regarding integration in kind of your R&D plans to maybe make this tighter – a tighter link with some of your existing products any things you can expand on there?

A little bit. Obviously it’s still early and so we have -- we have ideas around everything right and we spent a lot of time by the way studying this. We took a lot of time with this one, I personally spoke with a pretty large number of people around their company. Mike was very kind to give me access. To really try and understand I’ve been to the Sweden office, to the Toronto office in Boston talk with the guys that they’ve in [indiscernible] . So I think, we have some knowledge and understanding of what goes on there. But, until we really get in, I think and work together, we don’t want to be too disruptive here. I think, you have to go step-by-step. But, if you look at Panopticon as an example there – it’s our real-time data visualizations used by a lot of trading desks, in banks and such. Now, they’ve developed a streaming offering which is sort of the stage before the visualization. Like anything, it’s like a pipe where each stage is doing something in the final stage and in this case, is the actual visualization.

So they’ve just introduced a new product for streaming. Of course, with the units model, it makes it easier to use both of those products. If you’re already using the visualization now, you have access to the streaming solution as well which is I think a little bit of power under the model. We’re going to continue to focus and even add maybe a little bit of sales horsepower and technical support horsepower for the capital markets teams so that they can continue to focus on some market that they know and actually do even better within those markets. But, we’re going to take the core technology within Panopticon as really as just a core element, and bring it over to our SmartWorks team which is doing all the IoT development, the edge computing stuff and all of the other technologies that we have there and essentially integrate that within that overall solution. So, customers in our traditional world that are looking to do very similar things, right, very similar data will be able to do that with the IoT data. So, it’s really just blocking and tackling, it’s not as complicated as you might think. It’s a very strong team of developers in Sweden for Panopticon and so they’ve developed the code so that it is able to be leveraged in that way.

The Angoss technology I think is really considered one of the best technologies for machine learning and decision tree work in the market. And so there – we’ll do a little bit of work there to refresh the user experience I think and add some of the data prep technologies that come out of the monarch and swarm world into that tool. So those customers can have a better experience and of course those customers can just directly use monarch or swarm under the units model which they might not have been able to do before or even other tools that we might have.

The swarm product is a brand new product that they’ve just recently introduced and that lets you also distribute the analytics tools that are created by Angoss. And we think that that they’ve done a great job there and they’re probably going to integrate even more closely with the Angoss solution there. So just really continuing on the mission that

that – the team within Datawatch had. I think they had a reasonably good vision. I think these are really great products, by the way, the technology is just extremely strong. And I think within our organization with our ability to take a step back here try and shift them to a recurring licensing model and some of the additional development sales force power that we have marketing horsepower, the fact that we’re so global, they were not very global in the past just affords this very very nice business to really flourish.

That’s great. And one for Michael, if I could, not to put you on the spot too much here, but just want to get your impression of the HyperWorks units licensing model and your thoughts on the potential opportunity of converting your tools and software to that model? Thank you.

So short answer is I love it. The first time I met in-person with Jim and his team in Michigan and they described this patented licensing model to me, I said, do you license that to third parties because I would love to have brought it into Datawatch. I mean, it’s one of the challenges we have with these three complementary, but disparate solutions. And if we had something like that model in place I think we could have really blown out the expand part of our business. So I’m a huge fan and would love to – again would have loved to have licensed that patented solution eight months ago.

Great. That’s it for me. Thank you.

Operator: Thank you. Our next question comes from the line of Alex [indiscernible] with Deutsche Bank. Your line is now open.with Deutsche Bank. Your line is now open.

Yeah. Hi guys. Thanks for taking the questions. So I’m not that familiar with Datawatch, but just taking a look at their financials looks like they’re roughly breakeven from an operating income and free cash flow perspective at the moment. So what’s your expectations there? Are you looking for cost synergies as a result of this deal or do you think it’s actually going to be net investment as you grow the sales capability, do the integration of the products et cetera. So bottom line is this going to be earnings or and or free cash flow accretive in the near-term or actually possibly slightly dilutive? And then I mean in terms of philosophically that the whole logic here. Why did you think that this kind of an acquisition of an adjacent technology would be a better use of your cash than an acquisition in your traditional core simulation? Just be interested to hear the thinking there. Thanks.

So we’ll let Howard address the first one and then I can talk about your second question.

So the expectation as we look out over the opportunity to put the two businesses together is there are opportunities for synergies on – and really both levels, synergies from a cost perspective for sure. I mean the most obvious is you have two public companies here and at the end of the day you have one. And there’s other opportunities that – to be explored over time for sure. Do we expect it to be accretive based upon what we think is a conservative view over the plans and our plans are continuing to evolve as you might suspect. We think it’s could be neutral to slightly positively accretive in the very near – in the very near-term. But there’s a lot of hard work to do on all sides of the table in order to do this type ofcould be neutral to slightly positively accretive in the very near -- in the very near term. But there’s a lot of hard work to do on all sides of the table in order to do this type of transaction. But nevertheless there is – there is a clear path especially when you look at certain expenses that for example the public company really melt away pretty quickly.

And as far 00:35:50 the focus on this transaction I’ll let Jim speak to that.

Sure. You know three things, I think the first is that we really don’t see this as -- as far outside if you will and I know it looks -- it might look like it’s far afield but it’s really becoming more and more relevant because this convergence between high performance computing, simulation and data science is sort of been coming and ultimately they will be one if you will. I think in the future and we’re just anticipating that and making decisions in that context.

The second is we’re continuing to look at lots of more traditional we’ll say CAE and simulation. We just acquired some solid where we’re -- we’re very active let’s say in this space looking at a lot of things. Most of those are relatively small because it’s sort of the nature of the beast. It’s a very fractured market with a lot of different technologies. A lot of the larger players have been already acquired and some of the others that are – let’s say more moderate or less interested at this time.

Things change as time goes on and- yeah, I mean, I think that really just addresses the question.

Thank you.

Operator: Thank you. Our next question comes from the line of Alexander Frankiewicz with Berenberg Capital

Markets. Your line is now open.

Hi. Thanks for taking my question. Just looking at Datawatch’s product offering with the predictive analytics and anomaly spotting. Do you see any integrations potentially with smart site carriers going forward and does this change your competitive position within the IoT landscape at all?

We think that the technology is going to integrate within what we’re calling SmartWorks now. And that’s a little bit of a longer play for sure, but we do think it’s going to make us a lot more competitive. Yes.

Okay. Perfect. And then, do you see any other existing holes in your product offerings at all whether it be in IoT, High Performance Computing or Simulation that you’d be looking to fill in the next couple of years or so with the further acquisitions?

Yes, absolutely.

Perfect. Thank you.

Sure. Thank you.

Operator: Thank you. This concludes our question-and-answer session. I would now like to turn the call back to James Scapa, Founder and CEO, for closing remarks.

James R. Scapa

Chief Executive Officer, Altair Engineering Inc.

Yeah. I just want to thank everybody for getting up early and for all your support through our short public history here. Thanks everybody.

Operator: Ladies and gentlemen, thank you for participating in today’s conference. This does conclude today’s program. You may all disconnect. Everyone have a great day.

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