Chad Steelberg - Chairman and CEO Pete Collins - CFO.

Chad Bennett - Craig-Hallum Rob Stone - Cowen & Company Darren Aftahi - ROTH Capital Partners Mike Latimore - Northland Capital Markets Tom Diffely - D.A. Davidson Lee Krowl - B. Riley FBR Pat Walravens - JMP Securities.

Good afternoon. Welcome to Veritone's First Quarter 2018 Earnings Conference Call. After the market closed, Veritone issued a press release announcing its results for the first quarter ended March 31, 2018, and the press release is available in the Investor Relations section of Veritone's Web site.

Joining us for today's call are Veritone's Chairman and CEO, Chad Steelberg; and the company's Chief Financial Officer, Pete Collins. Following their remarks, we will open up the call for questions.

Please note that certain information discussed on the call today will include forward-looking statements about future events and Veritone's business strategy and future financial and operating performance, including its expected operating performance for the second quarter of 2018.

These forward-looking statements are subject to risks, uncertainties and assumptions that may cause the actual results to differ materially from those stated or implied by those statements. Certain of these risks and assumptions are discussed in Veritone's SEC filings, including its Annual Report on Form 10-K.

These forward-looking statements are based on assumptions as of today, May 8, 2018, and Veritone undertakes no obligation to revise or update them.

In addition to the company's GAAP financial results, during this call, management will be presenting and discussing the company's earnings before interest, expense, depreciation, amortization and stock-based compensation, or EBITDA, which is a non-GAAP financial measure.

A reconciliation of the company's EBITDAS to its net loss is included in the company's press release issued today. Finally, I would like to remind everyone that this call is being recorded and will be made available for replay via a link available in the Investor Relations section of the company's Web site at www.veritone.com.

Now, I would like to turn the call over to Veritone's Chairman and CEO, Chad Steelberg. Sir, please proceed..

Welcome everyone, and thank you for joining us today. Q1 was a great quarter for Veritone as we experienced an inflection point in our AI platform business.

Notably in the quarter, our AI operating system aiWARE saw the following year-over-year growth, and over 50% increase in active customers, and over 75% increase in net new customers, and over 500% increase in SaaS revenues, reaching our first 1 million quarter, and over 250% increase in cognitive engines integrated with our aiWARE operating system, almost a 1000% increase in total accounts, and 180% increase in total customers.

Our SaaS revenue growth is particularly noteworthy as it reflects the success we are beginning to achieve with our 'land and expand' strategy of making it easy and cost-effective for customers to deploy AI to enable 1x and 2x solutions to their immediate business needs, and then increasing our business with them as they realize the power of our platform and create additional used cases.

We saw significant growth in our second vertical market, legal, and made important stride in laying the groundwork for our third vertical, government. For our new followers, I would like to now provide some background on artificial intelligence and our business offering.

AI-based solutions can analyze large and complex bodies of data much more quickly and effectively than human's can, due to their superior processing speed and scalability.

Today, this enables these solutions to extend the user's cognitive capabilities, increasing their effectiveness, and in the future, it will allow these solutions to perform some human cognitive functions altogether.

This analysis is performed by cognitive engines, which are specialized machine learning algorithms trained to do certain things, such as transcribe spoken language or recognize faces or objects within videos. For these engines to be effective, the tasks need to be defined narrowly, and the engine needs to be specifically trained to performing.

For example, an engine can be trained to recognize spoken English speech, but that same engine would be incapable of recognizing French. The more specialized the engine, the higher level of accuracy.

For example, even within natural language processing engines, an engine specialized in a particular dialect or subject area will have higher accuracy in recognizing speech within those characteristics than a more general engine for that language. No one engine can do everything well.

As companies recognize this fact, over 10,000 of these engines have now been developed, and that number is growing exponentially. The challenge is that for most tasks, no single engine is capable of producing the required analysis at a sufficient level of accuracy.

For example, a law enforcement user may need to search surveillance footage for both faces and tattoos. For a conversation being transcribed, it may shift between English and Spanish, or a user may want to search for a specific individual speaking certain words.

To perform these tasks effectively, you need to select and employ multiple cognitive engines often across multiple classes and within different outputs. And then employ applications to use the data.

To solve this very complex technical problem we developed aiWARE, an AI operating system that orchestrates multiple cognitive engines, normalizes, correlates, and stores the outputs, and then integrates applications to search, use, and share the data, much as a computational operating system enables the computer's processors, peripherals and applications to work together.

At the heart of aiWARE is our unique patent-pending orchestration technology, which we call Conductor. Conductor uses AI to learn the capabilities of each engine on the platform and selects the right engine or engines and intelligently orchestrates them to achieve the best results.

Customers deploy aiWARE because it allows them to analyze information in all its primary forms, including audio, video, and text, at scale, and uses the results to meet their objectives with accuracy, speed, and ease.

Unlike monolithic systems such as IBM Watson, which can cost tens of millions of dollars and take months or more to implement, our customers can be up and running on aiWARE in under an hour for monthly fees as low as $500. They can begin their AI journey on a single project and expand as the business value becomes evident.

They could also develop custom applications to extend the usefulness of aiWARE for their organization's specific use cases. We have multiple partner communities in our collaborative ecosystem, developers of cognitive engines, applications, and data products, as well as system integrators.

The cognitive engines on our platform come from a wide range of companies, from small tech shops in the United States and abroad, to large public companies including Google, Microsoft, IBM Watson, and Nuance. We pay the engine developers based on the amount of media we process through them.

Our platform allows those engine companies, particularly the smaller ones, to focus on enhancing their engines and developing new engines because we provide them with revenue-paying customers. By growing the number of cognitive engines on our platform we also increase the accuracy of the cognitive processing our customers can achieve using aiWARE.

Similar to Microsoft's operating system or Salesforce's AppExchange, our open ecosystem allows application developers to write their own applications, and can be integrated with aiWARE and sold through our marketplace to enable users to use our platform to address specific use cases.

Similar to Salesforce, we expect to receive 30% of the licensing revenue from these applications. Similarly, developers of data products, such as Nielson, can offer their products through our marketplace and users can correlate them with their data.

System integrators use our developer application to build custom cognitive engines and/or applications for their customer-specific use cases so that they can use aiWARE to integrate the power of artificial intelligence into their operations.

For Veritone, these system integrators provide a connection to their existing relationships with major corporations and government entities that manage large amounts of unstructured content. A final aspect to the Veritone story is the kernel which started all of this, Veritone One.

Veritone One is both a high margin business that contributes significantly to our net revenues. And it also gives us valuable information about the needs of the media customers, and shows customers in that market how they can use artificial intelligence to improve the effectiveness of their media buys.

Now, I'd like to share a bit about what I'm seeing in the broader industry before turning it over to Pete for financial details. The industry as we know is in its early days.

Recent research from Cohen shows that 78% of users surveyed are actively planning to implement artificial intelligence, but only 16% of those companies were planning to invest in 2018. I am seeing three factors limiting customer participation in this industry right now.

First, the technology represents change and requires new thinking from potential users. It is also still at a relatively early stage in the development of its capabilities. Second, there is a lot of scar tissue out there. This is when an organization is hesitant to make significant investments in AI after their first initiatives failed.

We hear IBM Watson's name here the most. The third factor is trust. Humans are not ready to fully trust computers alone. Solutions like self-driving cars, where AI replaces human actions requires a huge amount of trust.

Augmented intelligence solutions that extend the users' cognitive capabilities rather than replace them are much easier for humans to accept today. Our strategy recognizes and addresses each of these barriers.

First, our aiWARE platform makes cognitive engines better and orchestrates multiple cognitive engines to deliver insights that exceed the sum of the parts. Customers can very quickly begin to see the value delivered by the platform.

Second, our technology is as future-proof as possible, which reassures customers that our solution will evolve with the technology and their needs. There is never a need to rip and replace, because the solution offers the optimal cognitive engines from our continually-growing ecosystem.

In addition, it can start integrating AI on a single project without a major financial or time commitment, and then expand their use as the business value becomes evident. Lastly, let's talk about the trust factor.

We are purposefully not yet going after the 10X solutions where computers are solely in charge, because the trust and technology are not ready for those yet. We are working on 1X and 2X solutions which use AI to extent the capabilities of human interaction and intelligence. This is what we call augmented intelligence.

For example, our technology helps law firms lower cost by finding the right audio, video, and text evidence hidden among a virtual warehouse of information much more quickly and effectively than other methods. And it helps broadcasters increase their revenues by enabling them to demonstrate and measure the value of they deliver to their advertisers.

Veritone makes it easy to start small and deliver AI wins to show the value of our solution. We believe that these small wins will expand over time as users learn the power of our platform, as has been the case with CBS Radio, iHeartRadio, and more recently ESPN.

For example, ESPN started using our platform in 2016 to analyze its national radio network programming of sports talk and live events, including the NFL, Major League Baseball, NBA, and college basketball and football.

This year they added television, simulcast, and podcast in their owned and operated radio stations in New York, Chicago, and Los Angeles.

The expanded use of our platform will address what ESPN describes as, "The rapidly multiplying demands for actionable media insights from brands and advertisers." Eventually there will be 10X solutions, but we expect those to happen over time and in a virtuous cycle with the participation of a growing ecosystem of companies and datasets.

We are really excited about the progress we are making in executing our strategy. But as I have said many times, we are in the very early innings of a long game. Now, I'll turn the call over to our CFO, Pete Collins, to walk us through our financial results and key performance indicators for the first quarter of 2018.

Pete?.

Thank you, Chad, and good afternoon everyone. Our net revenues in the first quarter of 2018 increased 25% to $4.4 million from $3.5 million in the prior quarter, and they increased 41% from $3.1 million in Q1 of last year.

The year-over-year increase in net revenues was mainly due to a 506% increase in SaaS net revenues from our AI platform, which increased from $209,000 in Q1 last year to $1.3 million in Q1 this year.

The increase in our total net revenues was also due to an 8% increase in our Media Agency net revenues, from $2.9 million in Q1 last year to $3.1 million in Q1 this year. Looking closer on our AI platform business, we generated net revenues primarily in two verticals in Q1 of 2018, those being media and legal.

The media vertical delivered the majority of the AI platform's net revenues in the quarter as we continue to build on the business development work we started in 2016. Our land-and-expand approach delivered the media verticals' revenue growth particularly at iHeartMedia and Entercom CBS Radio.

The legal vertical delivered the majority of this quarter's revenue increase on both the year-over-year and sequential basis. The legal vertical's net revenue were primarily in the eDiscovery or litigation support aspects of this market, which typically involves non-recurring project engagements.

Our largest project this quarter involved transcribing over 1 million recorded phone conversations on behalf of a financial institution. We processed this volume quickly and achieved a level of accuracy that was better than their other providers.

Our monthly recurring revenue or MRR under agreements that affected the end of Q1 increased 54% to $169,000 from $110,000 in the first quarter last year. The year-over-year increase of $0.2 million or 8% in net revenues from our Media Agency business was due primarily to the growth in the number of active clients.

We had 60 active Media Agency clients in the first quarter of 2018 compared with 39 in the first quarter of 2017, an increase of 54%.

The increased revenue from the growth in the number of active Media Agency clients in the first quarter of 2018 overcame a year-over-year reduction in revenue from one significant client that had a large initial campaign in the first quarter of 2017 that did not repeat this quarter.

Our gross profit in this year's first quarter increased 31% to $3.8 million or 87.1% of net revenues from $2.9 million or 93.7% of net revenues in Q1 last year. The gross margin of our AI platform business is lower than our Media Agency due to the difference in their business models.

So, as our AI platform grows to become a larger proportion of our total net revenues, we expect our gross margin will move to a level more typical of the SaaS model in a 65% to 70% range.

The change in gross margin was due primarily to an increase in cost of revenues related to the higher volume of data processed by our aiWARE platform during the quarter. Turning to our expenses, our total operating expenses in the first quarter of 2018 increased to 6% for the prior quarter to $17.1 million, and increased 79% from Q1 last year.

Both the sequential and the year-over-year increases in total operating expenses were due primarily to our higher headcount, particularly in software development, data science, and sales and marketing, which we expect will further enhance our aiWARE platform and drive higher AI revenues in the future.

Included in our total operating expense this quarter was $2.5 million of stock-based compensation, compared with $2.5 million in Q4 of 2017 and $125,000 in Q1 last year. Loss from operations in Q1 this year totaled $13.2 million. This compares with a loss from operations in Q1 last year of $6.6 million.

Net loss attributable to common stockholders in the first quarter of 2018 totaled $13.0 million or $0.81 per share. This compares with $6.9 million or $3.09 per share in Q1 last year.

The EPS figures are based on 16.1 million weighted average shares outstanding for Q1 of 2018, compared with 2.2 million weighted average shares outstanding in Q1 of 2017.

It's important to point out that our net loss for the first quarter of 2018 included the $2.5 million of stock-based compensation, as well as $355,000 of depreciation and amortization expense related primarily to the amortization of the software and technology repurchased in December of 2017.

Now turning to our non-GAAP metrics, earnings before interest expense, depreciation, amortization, and stock-based compensation, or EBITDAS, for the first quarter of 2018 was a loss of $10.2 million compared with a loss of $6.4 million in the first quarter of 2017, and a loss of $10.2 million in Q4 of 2017.

The higher EBITDAS loss compared to the year-ago period was due primarily to the addition of software development data science, and sales and marketing resources as I mentioned before.

While our EBITDAS loss was higher on a year-over-year basis, it was similar to the prior quarter loss, demonstrating the leverage in the model where we were able to increase our AI net revenues by 506%, and the whole costs relatively flat.

Now turning to our balance sheet, which remains strong, at the end of the quarter, we had cash, cash equivalents, and marketable securities of $54.5 million, and no long-term debt. Next, I'd like to shift gears to our Key Performance Indicators or KPIs, for both our AI platform business and our Media Agency business.

Our AI platform business exceeded our KPI guidance for the first quarter of 2018 across all four metrics. We had a record 70 customers on the platform at the end of the quarter, compared with 57 at the end of last quarter, and 25 at the end of Q1 last year.

In terms of total accounts on the platform, we had 591 at the end of the quarter, compared with 467 at the end of last quarter, and 57 at the end of Q1 last year. We had 184 third-party active cognitive engines on the platform at the end of the quarter, compared with 151 at the end of last quarter, and 48 at the end of Q1, 2017.

And finally, during the quarter, we processed 2.8 million total hours of video and audio files, compared with 367,000 in Q1 last year. The total hours processed this quarter nearly matched our total for all of 2017. As we grow and expand our AI platform, we will continue to provide goalposts to make it easier to track our success.

Along that line, we expect to end the second quarter of 2018 with 15 new customers, approximately 30 new accounts, and approximately 20 new active third-party cognitive engines on our platform, and having processed approximately 3.5 million hours of video and audio files during the quarter.

We expect that the growth rates for adding accounts will slow in Q2, in comparison of the trend of the past four quarters, because we've already on-boarded many of the large radio broadcast groups. For our Media Agency business, we evaluate three key performance indicators.

First, the number of new clients added under master service agreements; second, the total number of active customers; and third, the average media spend per client. During Q1 this year, we added 14 net new clients, compared with eight net new customers in Q1 last year.

In terms of active clients, we had a total of 60 as of the end Q1 of 2018, compared with 39 at the end of Q1 2017, a 54% increase. During Q1, our average media spend per client was $490,000 compared with $670,000 in the same period last year, which is a 27% decrease.

In the first quarter of last year, one client accounted for a significant share of the Media Agency's net revenues when that client launched its service. That launch campaign was not repeated this year. The significant growth in our active client count allowed us to increase our net revenues versus last year, despite the drop-off from this one client.

It's important to keep in mind that while this business is mature and provides the solid foundation for Veritone, it can also experience volatility in net revenues from quarter to quarter. That completes my financial summary. I'll now turn the call back over to Chad.

Chad?.

Thank you, Pete. At a macro level, AI use cases today carry massively heightened capability of compute with human interaction, resulting in comprehensive insights that solves key problems and has the capabilities to generate new breakthroughs within virtually every market and application.

I believe the market at large still needs to establish a greater level of trust of artificial intelligence, before wide-spread adoption occurs. Veritone's AI focus on enabling early and small wins for users to solve immediate business challenges, while leveraging the insights only humans can provide aligns with the market state-of-readiness.

We make it easy and cost-effective for customers to deploy AI to enable 1x and 2x solutions to their immediate business needs, and then increase their business with us as they learn the power of our platform and create additional use cases.

Note that the trajectory of our business will be both unpredictable and lumpy as a result of the industry dynamics. The industry is new. Some of our business comes from projects such as legal cases that are a varying revenue size and duration. When the case ends, the associated revenue stream from the project also ends.

As I had said, we are in the very early innings of a long game. And over time, as we continue to execute our strategy and build our business across all of our verticals, we expect to deliver significant, sustained revenue growth.

We are focused on continuing to develop the foundation of our AI platform business, including continuing to advance the proprietary Conductor and data science technology in the build-out of our best-of-breed ecosystem, which with new third-party engines, new third-party developed applications, and new volumes of data ingested will create what we see as an autonomous, virtuous cycle.

We are building our offerings in a solid manner and working to deliver meaningful and measureable value to our users and members of our ecosystem. Today, aiWARE is augmenting human technology, extending the users' cognitive capabilities while leveraging the insights only humans can provide.

Over time we expect to be able to enable our users and partners to deliver 10X solutions that can perform a greater range of human cognitive functions which will fundamentally transform the way these organizations operate. Again, thank you for your time today. We look forward to updating you on our progress on future calls.

We're now ready to open the line for questions.

Operator?.

Thank you, sir. [Operator Instructions] Our first question comes from the line of Chad Bennett of Craig-Hallum. Your line is open..

Great, guys. Thanks for taking my questions; great quarter, phenomenal to see the AI platform, huge growth sequentially and year-over-year; great to see, congrats..

Thanks, Chad..

Yes, no problem. I guess the first question, it's great to see that the legal vertical, it is -- you're starting to see traction there and it sounds like it was a meaningful contributor in the quarter. I understand that this is potentially a lumpy vertical for you guys based on it being project-based.

I guess, maybe for Pete, how significant was it in the quarter? And then, I know you guys have talked about before I think legal being your biggest vertical this year in the AI platform business. Is that still the case and how do you think legal plays out through the rest of the year? Thanks..

Yes, what we said in the remarks was that it was the largest contributor to the increase on a year-over-year basis, and also from Q4 to Q1, but media was the majority of the revenue in the quarter.

So legal had very good growth, we still think it's going to be the biggest source of revenue in the AI business for the year, but it's just kind of ramping up from a smaller base at the beginning of the year in comparison to media..

Got it. And then Chad, maybe you could talk about you guys made, I thought, a pretty interesting announcement around effectively real-time capabilities around your new version of our AI technology and aiWARE and your Conductor technology.

Can you talk about, I guess, from a competitive standpoint in the market how far ahead this kind of brings you? I mean, you guys are already, in my opinion, kind of leading edge in this area.

But just kind of the differentiation the new iteration creates for you?.

Absolutely, Chad. I mean, what we were seeing in the market with our 1 and 2x solutions were sort of -- anywhere between a five and 10-minute time lag between the intelligence across all of those different cognitive images that we could process and then deliver to our partners.

But both in the media industry as well as we started to work in public safety.

The capability and the 3, 4, and 5x solutions to be able to have near instantaneous cognition competitive with the human would really start to open up ways to protect our citizens better in public safety, as well as in media to take real-time actions whether it be in terms of digitally inserting a new advertisement, et cetera.

So the potential is really why we chased that technology. It took us nine months to actually go from a three to, again, multi-minute lag to now just a few seconds and trending even lower than that.

From a competitive standpoint there isn't really anybody out there that's providing multi-engine cognition at this level of scale, even at the three to five-plus minute range. So we're now down to the seconds, really working with our partners. So this isn't a competitive response.

We're doing this because our partners are demanding the need for this level of intelligence at this level of speed and accuracy..

Got it, makes sense. Thanks guys. Nice job again..

Thanks, Chad..

Thank you. Our next question comes from the line of Rob Stone of Cowen & Company. Your line is open..

Hi, guys. Chad, I wanted to talk about legal for a minute as well. You mentioned in the prepared remarks that you had a big project processing some recorded calls, and got that done quickly and with higher accuracy.

Can you give us a sense of sort of what kind of performance step-up are your legal customers looking for in order to get them to adopt this? And which is more important, the speed or accuracy, how does that affect their thinking relative to cost, for example?.

In the legal category, at least with the current use case for the discovery data processing speed is not necessarily the driver. It really comes down to accuracy and cost.

And today, historically firms have been paying a substantial premium to the service that we're offering by routing a lot of this information to humans to provide the transcription services against media files. And that bar, obviously, is extremely high in most cases.

So to win the business we needed to produce results that were substantially better than single-point solution engines on our platform, which was achieved using Conductor. So as we continue to expand the number of natural language processing engines from -- in nascent times, I think last year we were in 60 to 80 range.

We're now over 115-plus engines just in the category of natural language processing which gives us the breadth of both language as well as dialects to be able to parse and transcribe audio and video based files at a level that obviously the legal firms are finding to be acceptable, and clearly ahead of the competition.

From our last benchmark we were somewhere between 15% and 20% better than the single best point solution engine on the platform using Conductor..

So, you mentioned the non-recurring nature of these projects, but having proven that it's a lower cost and acceptable level of accuracy, can you give us a sense -- you have I guess established some channel partner [technical difficulty] in this area, what kind of sales cycle do you foresee to then sign up additional projects? Should that go fairly quickly?.

I think it's again going to be lumpy, not necessarily because the results weren't spectacular for the multiple channel partners that are using our platform today to prosecute cases, it really just comes down to, again, working with the law firm and in turn their clients.

Do they have the budget and the wherewithal to process this audio and video-based files, does the case match up against the technology we have in terms of how they want to handle the case. And that's something that's out of our control.

But as we continue to push and expand the number of system integrators and MSPs in the legal business obviously we will start to flatten out that curve as larger deal flow opportunities come to us..

Great.

A couple of questions for Pete, if I may; one, Pete, could you touch on customer concentration in the quarter, number of 10% customers or sort of roughly how the revenues broke down?.

Yes, I think in the Q, Rob, we've got disclosure in there. And I don't remember it exactly off the top of my head, but I think the top 10 customers were somewhere in the neighborhood of about 55% of the revenue.

So especially on the media agency side with the increase in the number of active customers, active clients they've got, they've done a very good job of kind of mitigating the risk of being too heavily concentrated in a few different customers. So as the business is growing we're seeing that dependence upon any particular customer being mitigated..

Great. And you mentioned the increase in staffing and investment in R&D and data science, sales and marketing.

Could you give us the headcount figures for end of '17 versus end of Q1?.

Yes, so at the end of '17 we had 206 staff members. And at the end of Q1 we had 225..

Okay.

And how should we think about the OpEx trend or headcount additions for Q2 versus Q1?.

I don't think we're going to see another 20 people coming onboard, 19 people coming onboard. I think there'll be probably a few targeted hires, but I'd say the run rate would probably be about a third of what we saw in Q1..

Great. I'll jump back in the queue. Thanks, guys..

Bye, Rob..

Thank you. Our next question comes from the line of Darren Aftahi of ROTH Capital Partners. Your question please..

Hey, guys. Thanks for taking my question. Just back to the topic of legal, just given kind of the lumpy nature of it, I'm curious the lead time on how fast you can kind of get these wins versus actually processing.

Said another way, can you have intra-quarter wins where you actually may not have it in the pipeline and hence could actually recognize a fair amount of revenue to kind of move the needle quarter-to-quarter. And then second question, around your fed ramp in process status.

How can you work with some of the constituencies within the government while you're in the "In Process" status until you get final sign-offs. Thanks..

Sure, with regards to the legal, absolutely. We can have very short sales cycles as the case deems necessary for the technology to be applied.

The ramp up time and this is probably the most impressive piece about the business that we did in Q1, we had multiple projects come through in the quarter, but the very large one Pete referenced, there was over a million recorded telephone calls we processed in literally just a few days, the entire batch of files.

So the scalability of our platform was put to the test, proved very beneficial to the law firm that was prosecuting the case. So this is not a function of scale, it is a function of really just continuing to educate the marketplace and allow those MSPs a very simple path on-boarding to our platform and using the technology.

And I think you'll see this continue to grow. The lumpiness is really going to come down to when we have those million-hour recorded opportunities hit deck we will be able to process them with our current technology and at scale. On the other side, the fed ramp piece for us, we've got authorization to test is a very large milestone.

It allows us to work and start to prosecute information with the Department of Justice and other federal agencies. Part of that though with each agency now have to go through a certification process to give us an authorization to operate, which is the next final piece.

We anticipate seeing those things start to happen with us in 2018, but they will be on an agency by agency basis. But our current status allows us to do business and generate revenue with agencies in the U.S. government..

And would those, follow-up on that, would those be more on a pilot basis or is it not limited to pilots?.

They will be on a pilot basis during the authorization to test phase, which we're in now..

Got it, thank you. Nice quarter..

Thanks..

Thanks, Darren..

Thank you. Our next question comes from Mike Latimore of Northland Capital. Your question please..

Thanks. Again, great quarter, nice to see the legal vertical tick in there.

In terms of additional legal opportunities do you see them coming through kind of a couple of resellers that are sort of fully trained or is it more about getting a few more of the service providers, resellers to onboard it as well?.

As we've talked about before, we've signed a majority of the large MSPs in the marketplace today. So very keen, down to the activation we saw in Q1, was about coming back through and retraining and pushing deeper into the education of what our technology can do that different than any other system out there.

That's what's really starting to break some of these cases loose for us. We anticipate that to continue in Q2. The other opportunity, again, for legal for us is not just the legal vertical, but it's legal and compliance.

And the compliance side is really what I talk about as being less of litigation, where we're working with banks and other institutions that require some degree of compliance that involves processing large amounts of unstructured audio and video-based information.

So from our perspective, I think we are heavily engaged with a number of banks and other financial institutions on the compliance side, and I would anticipate us in the balance of this year having some of those opportunities generate revenue as well..

And the compliance opportunity that tends to be more of a traditional kind of subscription model, or is it usage based as well?.

It will probably be more subscription-based, but definitely you see lumpiness in those industries as various internal events at these banks occurs and that requires them to process more content on an ad hoc basis..

Okay, got it. And then your guidance for kind of hours of media ingested, it looks like you expect it to grow nicely again in the second quarter.

Is that largely on the video or audio side, or what kind of visibility do you have into that sort of forecast?.

I think it's still primarily more on the audio side, Mike, I mean the video side of the business with TV broadcasters, cable networks is a growing part of the business, but especially with legal, a lot of the work we're doing in legal is more on audio file context today.

So you combine that with our existing run rate from a radio broadcaster perspective, and most of what we are doing is for audio work at this point..

Okay.

And just last on the R&D Group, of your 225 employees how many are in the kind of R&D Group at this point?.

So, at the end of March, we had 69 in the R&D Group..

Okay. Great, thank you. Great quarter..

Thank you..

Thanks Mike..

Thank you. Our next question comes from the line of Tom Diffely of D.A. Davidson. Your question please..

Yes, good afternoon.

Just a follow-up on the hours of video processed question, so when you look at the growth into the second quarter, does that require a host of new legal customers, or is it really just expansion of existing customers?.

It's really expansion of existing customers. The way the market is set-up is over the last decade, service providers in the legal eDiscovery business have relationships with the law firms, and as those law firms begin to prosecute cases, the MSPs are engaged to in the eDiscovery process historically dealing with text documents, e-mails et cetera.

As the body of evidence increases, increasingly has more audio and video associated with those legal cases training the MSPs to now be aware of the technology solution called aiWARE that allows them to analyze the audio and video in a very similar way that they have been doing the text-based documents is really that education process.

So while it might be new clients in terms of legal cases to the MSPs, from our perspective, the really bulk of the MSPs are already been on our platform for a number of months, and we are really lenient to them to further the education, so they can be more nimble and effective, and using our tool to prosecute those cases..

Okay, great.

And then, when you look at the average engagement, how long is it? And are most of your engagements today discrete projects or the ongoing engagements?.

So, again in the legal side, it's really project work, but if you think about legal and compliance, how we think about the industry, once you are in litigation, it falls in the litigation side. That is all projects work, they've got the operating system and they are constantly putting different cases through the various engines on the platform.

On the compliance side, it does have a much more subscription feel to it with banks and others being able to have a much more predictable stream of unstructured content for analysis..

Okay. And then, early you mentioned that government is going to follow behind legal here.

Are you expecting revenues later this year then from government?.

We'll have pilot revenue this year from the government is our expectation with significant ramp in 2019..

Okay, thanks for your time..

Thanks, Tom..

Thanks, Tom..

Thank you. Our next question comes from Sameet Sinha of B. Riley FBR. Your question please..

Hi, guys, thanks for taking my question. This is Lee Krowl filling in for Sameet Sinha.

First, just a product question; just a quick product question on the cognitive engines, just a rapid development in your product and the addition of new cognitive engines, just curious if you could talk about maybe, do the older cognitive engines become obsolete at any point, or do these things build on themselves, so any sort of innovation is just purely additive?.

That's a great question. It really depends on the engines particularly, but we do see engines that are no longer being innovated upon by partners can become obsolete, but in other cases, we have some engine on the platform that haven't seen a line of code change in probably a year.

They're still being orchestrated through conductor, and play a valuable role in the ecosystem..

So the kind of the engines that we are providing is net of those that get kind of decommissioned. So, there is some of that, but they drop-off, and then what we are presenting is just active count at the end of the quarter set of point in time..

Got it.

And then, just a financials question; can you maybe just talk about the cadence of cash burn throughout the year, and maybe just put in buckets of the mix of investments between engineering and kind of your go-to-market strategy?.

Yes. So I'd say there was a fair amount of ramp up in headcount going back into the second-half of 2017 and continuing into the first quarter of 2018.

So that's given us additional capabilities from both a product perspective through engineering data science, as well as from sales and marketing perspective in developing leads and really pursuing opportunities.

So we see that run rate is going to transfer -- that investments going to translate into additional revenues over the back half of the year, and we expect to be able to use some of that additional revenue to reduce the burn rate from the $10.2 million we've had over the last two quarters.

So I think by the second-half of the year, there'll be slightly moderated level of cash burn..

Got it. And then, my legal vertical question, just curious, it seems like once you are in with these MSPs, there is an opportunity to land and expand significantly, kind of similar analogy to these agencies in the media side.

Could you just remind us once you are in with an MSP in with the law firm and generating revenue, at the MSP level, are you an exclusive provider of your services, or do you -- you know, the MSPs customers have the option to choose someone else?.

No, we are not an exclusive provider to any of the MSPs that we have reseller agreements with. It's a very -- again competitive marketplace out there both with technology solutions from legacy providers like a Nuance, to again human levels of transcription offshore. Our technology is the best of breed that's out there.

So every single week, we are out there winning business in these legal verticals.

So, part of the issue why it took is a two-quarter delay to actually start to see revenue through here was, there was some contracts that were in place with various MSPs where they had pre-bought services from third-party vendors and they needed those contracts to burn off before they could actually spend money with Veritone.

So, some of those have now happened, and we are watching the budget start to shift from competitors and legacy providers to a modern AI platform..

Got it. And then the last question from me kind of more high level, but you guys have kind of talked about the deal pipeline in the last several quarters, you mentioned the deal to close in December.

Maybe an update on just you know, what the pipeline looks like and maybe timing of the potential acquisitions throughout the year?.

Absolutely. So, we continue to see M&A as a strong component to our overall growth strategy, but obviously it's extremely difficult to predict the deal timing. So going forward, we will not be providing M&A color primarily not to tip the hand of the marketplace in terms of what our strategy is, or impair our negotiations..

Got it. Good quarter, and thanks for the update..

Thanks, Lee..

Thanks..

Thank you. Our next question comes from the line of Pat Walravens of JMP. Your question please..

Great, thank you for taking my question.

Hi, Chad, can I ask you sort of a big picture question which is given the early stages of market on the AI side, how could the sales cycles work? I mean is it always partner-based? Is it direct? What kind of person you want to hire? Who do they call? What would they say?.

Absolutely. When you think about the S-curves of the company that's having rapidly expanding marketplace and growth, you know, when you start off in a start-up, you have business development folks.

It's primarily an education function, teaching about the product, teaching about the used cases, and then getting some early wins and using that as reference points to expand.

The business development effort then translates usually into a sales cycle, where you get away from that biz/dev kind of education process to a much more classic, lead-gen sales and marketing efforts that lets you scale much more cost effectively and shorten your time span from lead to close.

But then you have another phase, which is really when you start using channel partners. And you start to educate a marketplace that can start to build on top of your platform and extend the reach of your sales team. And then lastly, you have self-service, which is kind of the ultimate goal to SaaS platform out there.

So where we are as a company, I think we are in the sort of the transition phase of going from biz, dev, and education into customers to now a very robust sales process. We've hired some recent leadership both in product marketing as well as sales that can really start moving in that direction.

Second, we've taken a very strong move and made a strong move into the channel space in Q3 and Q4 of last year, and we're continuing to extend that, not just within the legal and compliance sector, but also public safety and media.

Self-service yet is not on our roadmap, but how our customers today I think what the normal experience would be in a sales cycle is that actually three to four meetings to close. The first meeting is still educational, the second meeting is really us to point a POC, proof-of-concept.

In some cases, those are actually paid POCs and others they're free, they last anywhere between 30 and 90 days depending on the opportunity. The third and the fourth meeting are usually negotiations to close. We see about a 70% close rate once we get a customer into a POC.

So we're really actively pushing not only our channel partners but also our internal team to move customers as quickly as possible into the POC to build and measure empirically the lift and value and ROI by using Veritone's aiWARE and our personal intelligence in their business processes..

Okay, that's super-helpful.

And then, secondly I am just wondering what you -- I've been impressed by Wolf's sort of research and productivity over the years, what do you have him and maybe his team working on?.

So, if I told you I'd have to kill you. But Wolf is sort of our secret weapon. He is our Chief Data Scientist. Anybody I think worth in terms of system automation and artificial intelligence knows of Wolf's science. We have a very high powered team based at Seattle that supports him in his core research.

He recently took a professorship at Stanford University.

So he continue to be a very active member of the academic community, but were Wolf is really headed for is as we move from intra class conductor, which is a difficult problem, but we have had actually tackled, to inter class conductor which allows now the multiple cognitive engine in different classes to be able to use simultaneously to make better optimization and decision support for our users..

Great, thank you.

And then, Pete, maybe one for you, and I totally get that this is relatively small businesses and hard to predict, but do you guys consider giving some sort of revenue -- 'guidance' is probably too stronger word, but perspective and did you consider and sort of what factors played into your decision?.

Look, Pat, to be clearly honest, we like to give guidance, but it's just difficult to be able to really predict with --- with the market being so dynamic, we just don't have enough data points to be able to lay it out there.

So what we've done is shifted to just providing the information about KPIs on a quarter-out basis, which is where we've got a better line of sight. And as the business matures and we get more data points, we can look to extend that horizon out even further.

But at this point, just makes more sense for us to be able to give the guidance, give information about things that we've got in our line of sight..

Okay, fair enough. Thank you for answering my questions..

Yep..

Thank you. At this time, I would like to turn the call back over to Chad Steelberg for any closing remarks.

Sir?.

Great. Thank you for joining us on today's call. We want to thank our employees, partners, and investors for supporting us as we as pursue our mission of building the AI operating system of the future. We look forward to updating you on our progress in our next call. Thank you, Operator..

Thank you, sir. And thank you ladies and gentlemen, this does conclude today's conference. Thank you for your participation, and have a wonderful day..