CXR Spotlight Synapse by TalentNeuron

Chris Hoyt: Welcome, welcome, welcome, welcome. This is the Recruiting Community podcast. I am Chris Hoyt, president of CXR. I’ve got with me today, on the road, he’s Captain Mobile, Gerry Crispin, who is the co-founder of Career Crossroads. Gerry, are you dialing in from a tin can today? What’s happening?
Gerry Crispin: I’m dialing in from my Airstream in Roscoe, New York, home of fly-fishing—which I don’t even know how to spell—but there’s a nice river nearby, and 40 or 50 cousins of varying ages are trying to use floaters to move down the river.
Chris Hoyt: I love it. Point of clarity: is it “fly” or “fishing” you’re having trouble spelling?
Gerry Crispin: I’m not sure.
Chris Hoyt: I don’t know how to fly-fish either. It’s a romantic idea. I think it would be really cool to learn, but I don’t think it’s my jam.
Gerry Crispin: Me neither.
Chris Hoyt: Well, I’m glad you dialed in. I know we couldn’t keep you away from this one.
For those who haven’t listened to an edition like this before, we do this special series called CXR Solution Spotlight. Today we have Matt McGuire, who is the SVP over at TalentNeuron, walking us through Synapse. This is their new AI assistant for workforce intelligence.
The way we’re looking at this: if you’ve ever wanted to ask a question conversationally, just in plain English—like, “Is demand for analytics skills in HR actually increasing?”—and get back something structured and evidence-based without having to dig through dashboards or tables to build it yourself, this is a segment you want to stay dialed into, whether you’re on a treadmill or fly-fishing. Doesn’t matter—just leave it on.
Matt’s going to show us how that works, and I think where it’s already reportedly changing decisions for TA and workforce planning teams, and where he thinks the whole space—we’re putting him on the spot today—where the whole space is headed. So we’re excited about that.
Before we jump in, we’ve got a few things we share every time. We’re streaming on the socials—YouTube, Facebook, LinkedIn. You can check us out at cxr.works/podcast, where you can see all the past episodes and learn about upcoming ones.
You can also like and subscribe. You’ll find literally hundreds of interviews Gerry and I have done with TA leaders and practitioners from around the world doing interesting work that touches on how we attract and recruit talent, as well as manage and lead global recruiting teams.
One last reminder: we are an ad-free labor of love. We even dial in on our vacations. Ideally, nobody’s paying to be on the show, and we certainly don’t pay anybody to join us. With all that, Gerry, are we ready to dive in?
Gerry Crispin: We are certainly ready.
Chris Hoyt: All right, here we go.
Announcer: Welcome to the Recruiting Community podcast, the go-to channel for talent acquisition leaders and practitioners. This show is brought to you by CXR, a trusted community of thousands connecting the best minds in the industry to explore topics like attracting, engaging, and retaining top talent. Hosted by Chris Hoyt and Gerry Crispin, we’re thrilled to have you join the conversation.
Chris Hoyt: Matt, welcome to the show.
Matt McGuire: Thank you so much for having me, Chris and Gerry. I’m really excited to be here, excited to chat, and excited to show off some of what we’re doing with Synapse. Also, for what it’s worth, Gerry, I’m from upstate New York—I’m up in Clifton Park right now.
Gerry Crispin: You’re somewhere in New York, so you’re at least close to me.
Matt McGuire: Yes—Hills. I know there are a lot of good fly-fishing spots.
Gerry Crispin: Yep, down 17.
Matt McGuire: All right, yeah. We spent a lot of time in the Adirondacks—that’s a huge place where folks are heading out to for that.
Chris Hoyt: Very cool. Matt, are you able to spell “fly-fishing”? I won’t try it on this one because it’s being recorded. That’s three for three on the show who can’t spell fly-fishing, so that’s awesome.
Well, look, Matt, for those who haven’t had the pleasure of meeting you before, or really getting to know the work you do or TalentNeuron, why don’t you give us a real quick escalator pitch—frame it up for us. What is TalentNeuron, who is Matt, and why are we listening to Matt today?
Matt McGuire: I’m Matt McGuire. I’m the SVP of Product here, so I lead product, user experience, and the product marketing functions. What we do at TalentNeuron—and the goal of my team, and really everybody here—is to help guide our customers to the future of work. The way we want to do that is by taking both an external and an internal view of your workforce.
We’re going to talk a lot today about labor market intelligence, because that’s the primary driver of Synapse today. But beyond that, what we look at is getting yourself to a place where you understand what your internal teams are doing—their job roles, the tasks, the skills within that organization—and then using that to drive workforce intelligence for workforce planning, organizational design, building out talent marketplaces, and understanding how you bring in the right people over time.
How do I build up the folks I already have in the organization? How do I redesign the way work is happening, with inputs coming from the external market—how skills are evolving, how tasks are evolving, how automation is changing our lives every day—and what effects that’s going to have on a given role? We want to bring all of that to bear to help you make better decisions.
Chris Hoyt: TalentNeuron isn’t a baby company—you’ve spent years building out what I think some people would argue is one of the most comprehensive views of the global labor market. So my first question is: what was the moment the organization realized the bottleneck wasn’t about the data anymore—it was about how people were getting to the information?
Matt McGuire: I like the way you phrased that. The way I look at it is: data is fantastic, but data without insight is almost useless. There has to be some interpretation layer on top of it, something that leads to a conclusion. We don’t want Synapse to just tell you exactly what to do—go hire this person in New York. What we want to do is take all that rich data and put insight on top of it. Where could you be looking for this talent? Why should you be looking in these places? How could you access passive candidates? What would the sourcing strategy be?
These are things you can’t just glean from data. TalentNeuron has been fantastic about having data for a long time within its SaaS platform, but we’ve relied on our research teams and our consulting to provide that insight—or on our customers themselves to bring insight to the data.
Now we’re sitting on new technology that lets us take that data, take the knowledge of the world, and start applying insight. Why should you hire for this role in New York? Why should you look at Atlanta as an alternate location? What skills are growing over time? Let me put that in a narrative you can hand off to your leadership.
Synapse, along with a number of other things, drives forward that idea of insight, which then turns into action. Action is really the third piece of the loop we want to put in place. But yeah, that’s the driver—how do we turn all that rich data into insight I can actually use?
Chris Hoyt: I want to talk a little philosophy here, because I know we’re going to pull up a screen and walk through it in a second. One of the things that stands out to me about Synapse is that it’s not just answering the question that gets put in—it’s walking users through clarifying scope items, like role, region, and level. Can you talk about why that guided step matters, that “human in the loop” moment, and what the organization learned while building it?
Matt McGuire: I think it comes down to this: more and more TA teams, TA leaders, and recruiters are trying to become more strategic in their jobs. They’re not just go-getters saying, “I’ve got a job rec, I’ve got to go hire, I’ve got a hundred job recs in front of me.” Let’s be smarter about that approach—that’s literally what our customers say.
“I want my recruiters to be more strategic. I want them sitting with the hiring manager, with the HRVP, saying, ‘Okay, I see this job rec you have. Let me tell you why we might want to make some tweaks, because you need a person in seat in four weeks, and we’re not going to get that—I have the data to back up that this is an 85-day average time to hire.'”
That’s data. The insight that comes back is, “Let me give you some alternative ways to think about this. Can we not go with this extremely hard-to-get skill and upskill someone instead? Can we look at an alternative location? Do they have to be based in Chicago—we have a hub in Atlanta. Can we think more broadly about this?”
So when you think about that human in the loop, this is an empowering tool. It’s not there to tell you exactly what to do—it’s there to empower talent acquisition teams to be more strategic.
Chris Hoyt: We’ve had some level of this intelligence for years—”if you adjust the salary a little, or move it 20 miles, it’ll fill more quickly.” But what we’re talking about today is different, and you guys have really blown that out. Can we go into a demo—talk about a workforce leader who’s using it to answer a question they couldn’t have gotten before, or couldn’t have gotten to fast enough?
Matt McGuire: I want to poke at that “fast enough” comment—this is also about speed. It’s about being able to say, “I have a hundred recs in front of me that I want to be more strategic with. I can’t spend the time digging through the tools, digging through the data, writing up reports.”
So we’ll load this up with a basic use case: “I’m in the process of hiring AI engineers. We’re a remote-first company looking to hire in the United States only. Where should I hire them, and what are the most in-demand skills I should be considering?”
These are the kinds of things that let me work with a hiring manager to make sure they have all the options before them, credibly backed up by TalentNeuron data. So we’ll run that now. In the background, this is all tied into TalentNeuron’s data—I’ll talk more in a few minutes about the sourcing and why we trust it. But what it’s doing is taking that input and saying, “Okay, I have this role someone’s trying to hire called an AI engineer.” We don’t all call them AI engineers—could be AI software developer, machine learning engineer, whatever it might be. So we look across a broader range of roles, pull out keywords, know we’re only looking at data around the United States, and bring skills into it.
We’re loading all of that against the TalentNeuron dataset and coming back with more than just data—insight. As this loads, you’re watching deep insight and deep data coming in. We’ll give it a second to finish here, but it’s trying to think beyond the question you’ve asked and push you further down the lane.
Right now we’re getting our skills data in. We’ve already got location suggestions coming through, some salary benchmark data—we’re really giving the full picture of what this role looks like. We’ll finish up with some strategic recommendations for what to do next, but more importantly, that’s not the end—now we can start to dig in.
So, within this executive summary: this is a really hard role—an average of seven candidates per open role across the United States. That’s data—something you can say to your team, “This is going to take a while to source.” We get our market recommendations and the reasons behind them—New York Metro being key here. It’s hard, but it’s got the single largest pool. San Francisco follows, then some tier-two markets. So this gives us that data background we want to bring to the hiring manager, to the HRBP, to make better decisions—this is your narrative around the “whys.”
Then we get a summary of locations and start to dig into skills. A lot of this is based on postings. We can dive into the data sourcing again, but what we’re pulling in is millions of postings globally—142 countries, every day, all day—harvesting them, de-duplicating them, bringing in the skills, the job titles, the locations, the descriptions, understanding everything about them. This is how we start to understand the core skills for this role that we have to make sure are covered.
More importantly, thinking back to the future of work—what are the emerging skills? Are you hiring for the role of today, or thinking forward, and what skills do you need to get your hands on for the future? This is the kind of insight you’d otherwise have to dig deep for in any other tool—we can lay it out upfront. Running through national salary benchmarks, we’ve got strategic recommendations, but then we can keep going—recommendations for gathering passive candidates. This is where the insight comes in again. This isn’t data you’re going to get out of a dashboard.
Chris Hoyt: Wait—sorry, I don’t want to interrupt, but I want to call out something for those who are listening and maybe not watching. The first thing you did was give an insightful data dump. But what you just did was ask it for strategic assistance—not just data. I want to be clear, because you just changed how people think about using the tool. You just asked it for sourcing and recruitment help.
Matt McGuire: Exactly—and this is where the insight piece comes in. No dashboard is going to tell you how to gather passive candidates. You can be the most seasoned recruiter or specialist in this area, and this will still help you within the context of the data. You have to look at New York—who are the folks with the most people? And better yet, this will say things like, “Amazon has the most folks, but we’re seeing a massive decline in their hiring over the past few months,” which means they’ve probably frozen salaries and aren’t offering much internal mobility. When you think about your employee value proposition—what you offer your own employees—these become benefits to use when going after someone at that company.
Look at this—a checklist. So this moves you from “let me share some data and insight” to “now let me tell you how to fill that role, and fill it faster.” For the sake of time I won’t run through it all, but there’s also university pipelines—if this is an entry-level role, who do I go to, where do I find those candidates? Who are the competitors in the space—both literal talent competitors and companies with the most AI engineers I should be looking at? All of this, just type it in, and it comes back to you.
In the future, this is going to generate presentations—things ready for leadership to see, like, “This is our location analysis right here.” We’re only a couple of months away from that.
Gerry Crispin: You’re not very far from it, given the data I’m seeing in front of me. I could certainly ask a few questions about how to prompt it to share the data in a particular way. So yeah, you’re close to that. It’s a pretty comprehensive strategy as you work your way through it. That’s a really interesting tool.
Chris Hoyt: Yeah, man, we just had a call along Gerry’s point—about 40 companies, all executive recruiting leaders for their organizations. We do these calls from time to time, and one discussion was about where they think AI will be most impactful within their realm before the end of the year. There was this level of wishful thinking—”if only AI could already do this or that.” One organization said market research would be the biggest disruptor for executive recruiting, from an intelligence and market-intelligence standpoint.
But this looks to me like it’s already checking nine out of ten boxes that the TA leaders on our call this week were saying, “Gosh, I wish AI did this.” They just haven’t seen it yet.
Matt McGuire: That’s exactly it. When we think about the data sets available to us today, “market intelligence” is exactly the right phrase—that’s actually how we brand this. It’s not just doing hiring analysis and saying, “Based on job postings and supply numbers, here’s your supply-demand ratio.” It’s about saying, “Here are your talent competitors, here’s their growth in hiring for this role, here’s their growth in these skill sets or technologies.” We have all of that data, and we can glean it here.
We’re talking about folks in the acquisition space, but this kind of data is business-wide. If you’re going through M&A activity and want to understand more about the technologies out there, we’re giving TA and HR teams the keys to be better business partners in that sense.
Chris Hoyt: Yeah, and not just that—we’re also talking about expansion. If I’m starting to think about where I want to build a new call center, or prop up an organizational hub, it’s got the data for that too. So, Matt, what’s the ideal talent segment this is geared around? Executive recruiting? Corporate planning? High volume? Manufacturing, call centers? What is it?
Matt McGuire: There’s really no limit to it at this point, because we’re not gathering data to support one industry over another. Our customer base spans pharma, fintech, manufacturing, aviation—we’re across all sorts of areas, so it’s not limited in any way. We bring in all the data possible so we can get to these insights.
I will say it’s primarily focused on what we might call white-collar jobs, since a lot of the signals for tighter, blue-collar manufacturing areas just aren’t as available. I’ll be honest about that. But it doesn’t reduce the ability to say, “We know from census data that I need to build a new plant in a certain place,” or “I’m looking for a place to build a new plant—where’s the supply of people with these skills?” We still have that data; it’s just not as robust. So really, we cover almost everything.
Chris Hoyt: And how does this play outside the United States? Is its strength 80% US, 20% global? Fully US? What’s the dynamic there?
Matt McGuire: No, it’s fully global. We support 142 different countries with demand data and supply data. We have graduate supply data in a handful of those countries, and we’re growing that. We have gender diversity data across the entire grouping, and more diversity stats across a good chunk of those countries as well. We’re global with our data. And one thing I’ll mention—coming along with some of those presentation pieces I mentioned—is we’ll also start opening up more web search. So if there’s an area where we’re not fully featured in our core data, we’ll be able to go out, with guardrails, to look for alternate sources in areas where we might be a little lighter.
Chris Hoyt: So interesting. I’ve got to ask—how’s the pricing structured for this? By organization? By seat? I see a query counter up on the screen—is it request-based? How do you build that out for everybody?
Matt McGuire: Today, this is available to all of our labor market intelligence customers, with a limit of 100 queries a month, and that’s free—that’s what comes with it. In the future, as we expand its functionality, we’ll move to a credit system. We’re also looking at a standalone option—so if you’re not a labor market intelligence customer with access to the SaaS product, there’ll be a standalone option coming as well, likely seat- or credit-based for the organization.
The goal is democratization of data—getting as much of this into as many hands as possible, so we want to be careful about not limiting or complicating that. All of our LMI customers currently have this option. It’s AI, so we do run into some hesitation with companies not being quick to adopt it. But the structure is free today.
Chris Hoyt: I love it. One more question for you. You’ve talked about a future where this level of workforce intelligence isn’t looked at periodically, but continuously—integrated into systems and workflows, informing strategy in real time, certainly for TA. If I’m a TA leader today who’s dialed in, what would you tell me? You mentioned presentations earlier—give me a little more meat on that bone. What does this look like a year from now for people who are paying attention?
Matt McGuire: What this looks like a year from now, thinking primarily about labor market intelligence and the TA side of things, is a fully integrated Synapse within the platform we have. So, side by side—I’ve pulled up a dashboard, and Synapse is sitting next to me giving me insight on that. Or, if you want to do all your flows through chat, Synapse will be able to generate those dashboards, provide that PowerPoint output I mentioned, and fill in the gaps on any data we might be lacking. We have huge data coverage, but there will always be patches. Synapse is your side-by-side—I used to work with a guy who called things like this his “little buddy.” That’s what Synapse is going to be. It’ll be there as you’re going through your searches, doing your location analysis, saying, “Hey, I’m noticing stronger growth in this role in this area—maybe consider looking over here.” We want it to point you in the right direction.
Looking further down the road, Synapse becomes part of a whole workforce intelligence platform—the whole planning piece. We’re looking at labor market intelligence today, but you’re a recruiter, and one of the fastest ways to fill a role is to look at your internal teams. So when you combine the power of something like our talent marketplace—these are the people I have in seat today, these are the skills I have—and Synapse can say, “I know you’re hiring for this role in New York, but you have seven people in New York who actually meet this,” they might be prime candidates. We want Synapse to integrate into all of that and provide insight across the board.
Chris Hoyt: I love it, I absolutely love it. Matt, where does everybody go to check this out?
Matt McGuire: You can drop right into talentneuron.com. You’ll see Synapse right there, and you can dive in or reach out to us. We’ve also got a webinar coming up in the next couple of weeks—we can get some info out to you guys about that.
Gerry Crispin: There are some vulnerabilities you could be tapping into as part of that market intelligence as well. It’s telling you where you could be successful in terms of manpower planning and all the rest, but it could also tell you where you might be vulnerable to losses—because other folks will be tapping into your people too. It could even be evaluating the losses you’ve already had. I think it’ll be fun for the people whose roles will be responsible for using tools like this.
Matt McGuire: It’s funny you bring that up, Gerry—I totally agree. One of the conversations I had recently with one of our product managers was about the amount of context we can bring in about your own company. If we know who you are, we have labor market intelligence on you, and one of the ways people use the platform is to do internal competitive assessments—looking at themselves and comparing to others. Being able to provide that context—absolutely, I love that idea too.
Chris Hoyt: It seems like that’s the next level—you can give the C-suite a heads-up on where we’re bleeding talent that my talent planning teams may not even be aware of yet.
Matt McGuire: Yeah, and we can do that in dashboards today, but getting it into Synapse is definitely in the plan.
Chris Hoyt: Very cool.
Matt McGuire: Very cool.
Chris Hoyt: Well, Matt, thank you so much for joining us. This has been such a cool look. For anybody listening—hit replay, listen again, go through it. You can check out this and other episodes, not just Spotlights, at cxr.works/podcast.
And Matt, thank you very much. I know you’re a super busy guy—we appreciate you making time for us. Much gratitude.
Matt McGuire: Thank you very much, Chris. Thank you, Gerry.
Chris Hoyt: All right, until then, we’ll see everybody next week.
Announcer: Thanks for listening to the Recruiting Community podcast, where talent acquisition leaders connect, learn, and grow together. Be sure to visit cxr.works/podcast to explore past episodes, see what’s coming up next, and find out how you can join the conversation. Whether you’ve got insights to share or want to be a guest on the show, we’d love to hear from you. If you’re interested in learning more about becoming a member of the CXR community, visit us at www.cxr.works.
We’ll catch you in the next episode.