As the pace of business accelerates, companies need technology that not only keeps up but stays ahead. Go behind the curtain with PROS product leaders as they debut the newest AI agents embedded in the PROS Platform—digital teammates that sense change, decide in microseconds, and execute at scale, empowering businesses to navigate today’s dynamic and volatile market conditions with speed and agility.
Featuring:
- Sunil John, Chief Product Officer, PROS
- Ajay Damani, Executive Vice President, Engineering, PROS
- Greg Davoll, VP, Product Management, PROS
- Justin Jander, Senior Director, Product Management, PROS
Full Transcript
Sunil John: Hi there, everyone. And as Colleen said, welcome to day two of Outperform 2025. Yesterday, you were introduced to the focus we’ve had on agents and how much we believe the next leap in AI will be centered on how we collectively apply our creativity to make these agents help us in every commercial decision that we make. Today, I’m excited to be on stage with AJ and the team to show you demos of our agents representing the amazing work that we’ve been doing for you over the last six months, and talk to you about the way we’ve approached building our agents and why. Yesterday, if you had a chance to watch Rick Bradbury’s keynote on the next revenue super cycle, he walked through a bit of history to show you how customer interactions were unlocked with each technological shift. I’m gonna walk you through a similar timeline, but from a technology lens. Between 2007 and 2008, we came to know the iPhone and then the App Store. Prior to that, many people had phones, but they primarily used them for calling and messaging. The apps that we use were the ones that came from the manufacturer. The iPhone and the App Store opened our eyes to what an integrated hardware and software experience, a mobile optimized operating system, and an ecosystem of app developers could make possible.
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Sunil John: Now we have a multitude of apps that we carry around in our pockets. And from a work perspective, we were untethered from our desks. Cloud computing was another such moment, which began a few years earlier, but really started to take off in commercial practice around 2010. Prior to the advent of cloud computing, we had to procure hardware. You guys will remember the days when we had to set up our own data centers. We had to seek investments for CapEx purchases, and major software projects took a long time as we waited for hardware. And today, we can just get started with a credit card and elastically scale our compute needs up and down. This dramatically changed the way we build software, how we bought software, and the types of applications we can envision. Our AI, based on numerical models, really began to thrive during this time, as we were also able to elastically handle larger and larger data sets and glean insights for you. And today, we’re in this world of agents. And this couldn’t come at a more opportune time. For every offer that’s made, your customers are looking not only at the offer and what the products are, but the precision of the numbers.
Sunil John: And this is why numerical models combined with language models are so important. The accuracy and the precision of the numbers is what’s gonna drive that customer to actually make a purchase. And today, it’s harder than ever, because buyers are educated more than they ever were before. While they understand all the variations of products, you also have more products and capabilities and configurations than you’ve ever had before. That makes the world very complex. Volatility is here. In the things that are changing, prices are changing. Many, many other options are changing from all of your competitors. These are things that are happening daily. And as volatility changes, all of these things need to be factored by your customers. These signals are happening at a faster and faster speed, but they’re hard to keep up with. Not only are they hard to discover, but we usually don’t have time to process the implications of the signal. Not without language models and numerical models working together, to know whether it’s significant or insignificant, and how we should leverage this model. All of these things are increasing, and they’re happening very, very fast. So, in order to make sure that we don’t miss out on these opportunities that each signal would reveal, we have to make sure that we combine these. And we’re very excited to introduce the next leap forward with our agents that combine language models and numerical models.
Ajay Damani: So, the next leap is really agentic AI. And here, agentic AI is AI working side-by-side with your teams to move faster, smarter, and with intent, thereby scaling human productivity from 1X to 10X to 100X. But, what makes this leap possible isn’t just better AI. It’s a clear set of principles on how AI should operate in the enterprise. Every agent is designed with a business goal in mind. It’s not just to complete tasks, but to achieve very specific goals, advancing your business with true intention. And to achieve that goal, AI agents must be able to act autonomously. Our AI agents are intelligent actors that observe a reason and they act. And they operate independently to drive outcomes while staying fully aligned with your business context. But as we know, the context is always changing. And so, our agentic AI is built to be fully adaptive in real time. It’s learning from patterns, from signals, from shifts in the environment to stay relevant, responsive, and fully effective. And as these AI agents become more capable, they also must be very responsible. And so, what we’ve done is, we’ve built transparency and traceability into every layer of our platform.
Ajay Damani: Every decision is explainable. Every action is auditable, so you can trust what’s happening and why it happened. And finally, agentic AI is built not just to think, but to operate securely, reliably, and at scale. This is enterprise-grade AI. These five principles aren’t just ideas. They’re the foundation of everything that we’ve built. And today, we’re proud to show you what agentic AI looks like in action. So, with that, it’s my pleasure to welcome Greg Davoll and Justin Jander to stage to unveil the new agents that we’re launching right here at Outperform.
Greg Davoll: Hey, everyone. My name is Greg. I’m a sales rep for Blue Sky Sports. We’re a ski distributor based in Denver, Colorado. We work with thousands of ski shops in North America. So, great news. Yesterday, I got a call from a guy opening a new ski shop in Winter Park, Colorado. He needs 200 pairs of downhill skis, wants a mix of genders, mix of abilities. And so, my job is to come up with the winning quote for my customer. Fingers crossed, but he wants his quote in about 15 minutes. So, we’re gonna work through this pretty fast. So, here at Blue Sky, we use Smart CPQ from Pros along with Salesforce. And I started working on this this morning because I was so excited, but I didn’t get very far. So, I just created the shell of the quote. What I’m gonna do is show you traditionally how I’ve built out a quote, and then I’ll show you a better way. So, traditionally, I will navigate through a catalog. I’ll look through the skis, add the quote, bounce around a few categories, get a nice collection. The problem I always have is I know a subset of the catalog.
Greg Davoll: We have tens of thousands of skis, snowboards, outdoor equipment. And so, it’s impossible for me to know everything. So, last week, thanks to Pros, I discovered this new sales agent. And one of the cool things is this sales agent can help me find a product and a set of products so quickly. So, let me show you how it works. I’m gonna take exactly what Scott told me on the phone from Moose Rentals. He said I need 200 pairs of downhill skis for a variety of skill levels for both men and women. All right. So, at this point, what the agent is doing is it’s parsing my request, my question is pretty easy to type. There’s a few things going on here. One is it’s looking through the catalog, leveraging the LLM to find a nice blend of downhill skis. It knows that I need a variety of levels. That means beginner, intermediate, expert. It also knows that I’m looking for some gender-specific skis. So, this looks great, at least the beginning. So, the women’s downhill skis, that tells me at least understood the gender part. And I know this first ski, this is what my wife skis on, the Black Pearl 88.
Greg Davoll: This is a great one of our best sellers. So, that’s a good pick. I’m not familiar with the Shiva so much, but looks like it’s good on groomed and powder and a good length. Coalition, Nordica, another one I’m not super familiar with, but looks like a great ski. And then, there’s the men’s downhill skis. So, some of the fan favorites, QST, K2, and the Rustler. So, looks like an awesome start. And I told Scott I’d have this quote over to him before 9:00 a.m. So, I’m just gonna go ahead and ask politely. It’s always nice to be polite. Can you please add a mixture of all these skis to the quote? And I’m gonna remind it that I need 200 pairs. It’s not bad just to remind it. And so, at this point, and I’ll go ahead and minimize this, but it has added the skis and it’s actually chosen a distribution. So, just like any other quote, I can come in here, edit the quantity, edit the price, but this looks really good to me. It’s got a nice blend. It’s an even distribution, but I’m gonna just share this with Scott. And instead of putting together the paperwork proposal, I’m just gonna share the live quote with him.
Greg Davoll: So, Scott’s got a really nice and easy email address. I’m gonna give him read rights so we can collaborate on this and he can make some changes. Normally, I would send this to him via email, but since you’re all here watching, I’m just gonna go with the link. And this is actually a microsite, which has now been populated. It’s real time, both directions. So, this live quote is what Scott will see when he picks up the email and clicks on the link. So, Scott’s familiar with skis, right? He’s opening a ski shop. So, one of the things he’s gonna do, he loves these black pearls. He doesn’t need quite that many, but let’s say he needs 35. So, he can make that change. That updates real time. So, Greg, back at Blue Skies, gonna see that. But he remembers that he forgot to tell Greg that he needs some children’s skis. That’s a problem, right? A lot of families visit Winter Park. So, he sees this prompt or this agent. This sounds like something that will help him. And this, in fact, is the same agent I just showed you, but now Scott is interacting with it.
Greg Davoll: And Scott is gonna say, I need, please recommend, let’s go with that one, please recommend downhill skis for children. And I’m gonna say a variety of sizes. So, that means lengths, right? Size, length. So, at this point, same thing’s going on. The agent’s figuring out what’s in the catalog, what’s appropriate for children. What are the different sizes? And Scott is driving this. So, this is true self-service. And in a second here, I’ll get some recommendations on what those skis are. And I wanna inspect this. So, I’m Scott still, and I know a lot about skis. So, these all ring a bell. Rossignol Center Souls 130. I see a 76, 155. Armada’s a killer ski. The Volkl’s, oh, and the Bent Chettlers. Love those. So, there’s a lot of recommendations here, but it’s good to have diversity, right? Kids come in different sizes. So, let’s just say, sounds great. Please add a mixture of the skis above to the quote. And I’m gonna go with 200 pairs again just to start there. And just like last time, it’s going to take the skis from above. It’ll figure out a distribution that seems appropriate. And those have been added to the quote. So, at this point, I’m ready to go. I’m gonna text Greg, tell him to get me over the final paperwork. And I really want to get these skis in the mail by the end of the week. Justin?
Justin Jander: So, you all probably thought I really wasn’t paying attention the whole time during Greg’s presentation, but I am actually a travel agent. And one of my best customers is Blue Sky. And while Greg was doing all those things, I’ve actually been talking to them because Blue Sky is also planning their annual sales kickoff in July. And just in case you wondered, their kickoff happens in July because it’s their fiscal year, not the beginning of the year. So, while I was over here, I talked to my contact at Blue Sky. I understood where they want to go. Their sales kickoff is in Vegas. Sounds pretty good. So, I’ve worked with them on the dates that they want to be there, and I need to make a group booking for them for the sales team that’s of size 20. So, this is the interface. I’ve typed it all in, so you didn’t have to watch me type that. And I searched for the flights. Now, the GSO goes out and finds the best flight options for me, and I can determine what works best for my customer about Blue Sky. So, when that comes back, I know they want to leave early in the morning out of Denver, where they’re based.
Justin Jander: So now once I click the outbound, it comes back and reprices based off of the outbound price. And once that is selected, we can come down here and select the return. And I know that they told me they want to come back late in the evening on the 14th. So, I come down, and I find the last nonstop option. And from there, I click Preview Offer. So, now, as their travel agent, I’m responsible for a few different things. So, one of the things I’m responsible for is helping them make the booking. The second thing I’m responsible for is following up with them. I send them an offer. So, here you can see the offer has been generated. I make sure that gets over to my contact at Blue Sky. And they’re able to think about this, decide if this makes sense for them and all the things are what they want. So, this has been sent over to them. And now I’m gonna save the offer for later. Now, that’s one of my responsibilities is making sure that process is all done.
Justin Jander: Now, the other part of my responsibility is now my customer is holding that offer. But I have a lot of customers. So, I have customers holding a lot of different offers and several customers that also have bookings that have already been made as well. So, I come over here to my task queue. And this is all the work that I have that are my responsibilities. And this is a mixture of offers and bookings that are outstanding. And normally, I have to sort through all of that and make sure that I’m understanding who is up next and what is the most important thing for me to work on. But now I have the agent to work with. And so, with the agent, I can say, give me my top priorities for my offers. So, normally, when I didn’t have this tool, I’d be going out and sorting through the list, filtering the list, looking for what’s most important to me based off of what my intuition is and what I’ve been working on before. Now, in this case, the AI agent now is able to go out, understand the tasks that I have at hand, and then look at all of those and return back the most important priorities that are important to me.
Justin Jander: And as a travel agent, the most important thing for me is make the bookings so that I get back the money. Ultimately, I want money. I’m a travel agent. I wanna sell that business. So, you can see here, the system returned back some offers. And imagine here, for the sake of the demo, that we advanced a few days and the offer is due for Blue Sky. And with that offer due in two days, you can see that the system went through and the agent went through and understood what the most important offer is and understood how I need to react to that as quickly as possible. So, quickly, without even having to filter and sort through lists, I was able to see what’s the most important thing I need to work on. And now I can click on the offer, go and send that over to Blue Sky and remind them that they need to fulfill that offer and make it into a booking. Well, that’s great, right? But that’s one example. But also, remember, I’m not just dealing with offers. I also have the bookings that have been made. So, let’s say, show me my booking priorities.
Justin Jander: So, now it’s gonna go out and look for the bookings that have been made. Now, if you’re not familiar, the travel agent is able to make bookings on an airline for their customers, and the passengers or the group doesn’t necessarily have to pay upfront. So, in those cases, I have some priorities that I need to get through. Whether it’s collect final payment, collect deposits, collect names for the passengers. Those are all important things to ensure that my customer doesn’t incur extra fees or even have their booking canceled entirely. So, while the system is out there looking, it’s trying to find the most important bookings for me and find the ones that are most important to my customers as well, so, I can make sure that they’ve seen the results that they need to see whenever they’re working on this. And it’s a very important part of the tool because there’s a lot of information that it’s gathering and going through, looking at the value of it and looking at the importance of that customer to me. So, you can see here, the final payment is due.
Justin Jander: We see a couple of different things with deposits and final payments. So, the system is able to synthesize all of that information and bring that into a view that allows me to understand what’s most important to me. And that’s really most important to me, but it’s also most important to the airline. As the airline, you wanna make sure that your information is surfaced so that you get those bookings that you want out of your group passengers. So, I’m gonna turn it back over to Greg and he’s gonna take us through a few more things on his side.
Greg Davoll: Awesome. Thanks… So, fast forward, it’s Labor Day. Scott up at Moose Ski Rentals got all his equipment late August. He’s got them tuned, set up in his shop, ready to go. But there’s about 10 weeks or so before ski season truly begins. And he texted me this morning. And what the text said is that he wants my recommendation on some Nordic Skis. There’s a few great cross-country places up in Winter Park. I don’t blame him. Be a good business opportunity. But the problem I have as Greg, the sales rep at Blue Sky, is I don’t know much about Nordic Skis. So, instead of going and searching their catalog, we’re not at that point yet, I’m gonna leverage another new agent, the Insights agent from Pros, that I also discovered recently. And what this is gonna do is just let me type in a simple question, because that’s all I have, which is, can you please create a chart with the top five Nordic Ski products by revenue? Pretty simple, right? But that’s natural. That’s the question that I wanna ask. And the agent at this point, there’s a lot going on, right?
Greg Davoll: So, this is essentially going and discovering data, which lives in databases. There’s SQL involved, but you don’t see any SQL here. There was just that simple English question. And it’s trying to figure out, of course, it’s doing some sorting. Hopefully, I’ll get a chart. I’m not quite sure what kind of chart. I didn’t specify that. But from my interactions with this agent, it seems to prefer bar charts. And so, it retrieves that data, pulls that back up, and hopefully I’ll see a bar chart or a pie chart or something that gives me just a few nuggets of information. Okay. So, it got a little hung up on that. I’m gonna try, let me see, create a chart with the top five Nordic Skis by revenue. Occasionally, you have to ask it again.
Justin Jander: You can tell Greg’s very nice to the agent.
Greg Davoll: Maybe I should have added another please. So, yes, and so it is going through the process of querying the database, taking what it finds, sorting, trying to create a chart from the raw data. And so, wow, here we go. This looks perfect. So, what I have is the top five Nordic Skis. It’s pretty interesting. I see not much difference in revenue across these. But what I needed help with was really the make and model, right, the brand and model. So, as the rep, I just needed to know that Fisher is the brand to recommend. And I see here that S-bounds are top seller across Blue Sky. I’m definitely not sharing this data with Scott, but I’m gonna answer his question and recommend the Fisher S-bound. And just for diversity’s sake, I’m gonna throw in the Solomon Escape in a few different sizes. So, I’m gonna get back to Scott now and turn it back over to you.
Justin Jander: All right, so I’m gonna ask you to suspend reality for a moment. I know I was just a travel agent a few minutes ago. Now I am also a sales rep for Blue Sky. And last year, I was the second best Blue Sky sales rep. Greg was actually the top. But this year, I plan to be the best. And so, Blue Sky actually sent me to the top conference where I can learn to outperform that happens to be here in Vegas. So, imagine I’m a Blue Sky sales rep sitting where you are right now learning about all the great things that I’m gonna have in my hands this year. So, I know I’m gonna win this year, and I’m gonna beat Greg as being the top sales rep. He doesn’t know about all this. I’ll probably tell him afterwards, but we’ll see. So, now I’m sitting in the audience. I’m thinking, you know what? I’m feeling so confident. I want to leave from Vegas and go have a little short vacation to have some fun. So, I’ve been browsing Instagram over the last few days, and I keep seeing ads for my favorite airline, Wanderlust Air, and I’m getting excited.
Justin Jander: So, I click on one of those ads, and I land on one of the custom landing pages that Wanderlust uses for their website. And so, already it knows that I’m in Las Vegas, so it’s defaulted to information about Las Vegas. And so, you can scroll through, and you can see different ways that it’s telling me about the content, the offers that Wanderlust Air wants me to see. And I get down, and I actually see they have an inspirational shopping agent in their system. So, this is great. I really like the idea of using this inspirational shopping tool. So, I’m gonna say I want to leave in two days to go to the beach in the U.S. Where can I go? So I run that, and without telling it, I’m in Las Vegas. The system’s gonna know that I’m starting in Las Vegas. The system’s also going out and figuring out where beach destinations are. So, you can see the results have returned pretty quick, and it says it knows when I’m leaving based on the fact that I said leave in two days. That’s pretty cool, right? It comes back with some beach destinations.
Justin Jander: I’m not sure how nice the beaches are in San Francisco, but indeed there are actually beaches there. And a few different options. Sometimes the results, another day when I was trying this, it came back with Chicago, which I’m not sure anybody’s swimming in the, I guess they have beaches there too. But anyways, it looks up and understands where the beaches are and gives you those options that make the most sense for you. Now, it turns out I don’t live in Las Vegas, so I don’t really need a round-trip ticket. So, I’m gonna say leave in two days on a one-way trip to go to the beach in the U.S. And where can I go? So now the system’s gonna go back out, understand where I want to, what my options are now with a one-way trip. And the important thing about the agent here is it’s pairing together the information from the airline itself, so it understands schedule and pricing and that information. And then, also includes the information about what a beach destination means. So, it has to find both of those pieces of information.
Justin Jander: So, now we’ve got a few good options that are coming back, and those all look really good. However, it turns out I came to Vegas, I forgot my swimsuit. So, probably shouldn’t just leave from here to go on a beach destination. However, I never leave home without my size 12 hiking boots. So, I think what I’m gonna do is say instead of gonna the beach, I’m gonna go hiking in the U.S. So, quickly just change that. Now the agent is going out, understanding what a hiking destination is, and it’s gonna bring me back results that are relevant to hiking. So, it quickly shows me some cool places, Phoenix, Denver, Salt Lake. Those are interesting. I’m from Denver, so I’m probably not just gonna go back there. I want to go somewhere more interesting. And so, now I can see some options. And I have these options here, but just to show you the additional power here, let’s say I also said, where can I go for under $40? So now, I can run it one more time. The agent goes back to the pricing, understands where I can go for under $40, and it’s narrowed the results down to Phoenix.
Justin Jander: That’s perfect. That’s exactly where I wanted to go. The inspirational shopping tool helped me find that, and I get to use my size 12 hiking boots to go hike in Phoenix this weekend. So, I’m excited about that. And again, we’ve had a chance to show you a few different agents that we’re working on. And really this has been, the tools that we have are really focused around both the users of the pro systems as well as passengers and the customers that we have as Blue Sky and as a travel agent. So, you can really see the power of these agents. So, with that, thank you very much. And we’ll turn it back over to Ajay.
Ajay Damani: Awesome. Thank you, guys. Wow. I hope you’re able to see how these agents truly work side by side with your teammates to drive those business outcomes as well. And as you’ve seen, agentic AI truly unlocks boundless productivity by turning goals into outcomes. It scales human potential by removing a lot of the manual and mundane so your teams can truly focus on strategy, creativity, and impact. And finally, accelerating business agility by adapting in real time and helping you stay ahead of what’s next.
Sunil John: This combination of what you’ve seen is the power of combining the approachability of large language models with the precision of our numerical AI models focused on recommendations for price, for product, for nudging the sale along. All of these things are what’s possible today. We had some great demos up here, but we also have some great sessions for you throughout the rest of the day, and I hope you get a chance to attend these and see some of the agents that weren’t shown here in this particular session. Over the coming months, we’re gonna have more and more agents that we’ll be unveiling. In fact, I think from feedback from the team at the demo booths yesterday, there was a lot of you that inspired a lot of new ideas, and I think you’ll see a lot of genesis of additional agents that started right here. I hope you get a chance to explore this frontier with us through our preview program. Together, we can redefine what’s possible. Thank you.
Ajay Damani: Thank you.