Contextual Intelligence For Contact Centers

Your contact center already tells you what’s happening. The harder question is why and what you should do next. From the Enterprise Connect floor, we sit down with Ray Bohoac CEO of Spearfish.ai to unpack a practical approach to contextual intelligence that connects customer conversations to the back-office data that actually explains outcomes.

We get specific about how Spearfish moves teams beyond classic contact center KPIs like service level, QA, and CSAT, using a “signals” architecture that learns from calls and correlates them with systems like ERP, sales, and operational data. Ray shares a standout customer story: an apparel brand hears repeated complaints about a shoe wearing out, then traces those calls to the exact product and lot number, tracks the issue into the supply chain, and gets proactive with customers before the problem snowballs. That’s root cause analysis built for speed, not a report you read a month later.

We also talk about reality: multi-vendor environments, legacy tech, and a market crowded with agentic AI companies. The big takeaway is the feedback loop. When AI and humans do more work automatically, you still need a way to measure what changed, what worked, and what needs adjusting in real time across support, operations, training, and marketing. Ray also highlights expansion into non-traditional “contact center” settings like 211 organizations, proving the same foundation can drive mission-critical outcomes.

Subscribe for more conversations on contact center innovation, customer experience analytics, and applied AI, then share this episode and leave a review. What back-office data would you connect to customer calls first?

Transcript

SPEAKER_01 0:01

And it's Evan here at Enterprise Connect with Ray from Spearfish. Ray, how are you?

SPEAKER_00 0:05

Hey, great, Evan. Good to meet you.

SPEAKER_01 0:07

I always love connecting with startups, and you guys have a such a compelling story. Maybe introduce yourself and the journey at Spearfish.

SPEAKER_00 0:14

Sure, yeah. So uh Ray Bock been in the uh contact center space for for quite a while. At Spearfish, we've we've realized that there's new tools, new capabilities to help customers identify the root causes of uh things within their business. So we've created a contextual intelligence platform uh to help contact centers get out of operating as a silo. For decades it's been an island, right? But the customer communication is the tip of the spear. Uh and if we can pull in data and bring in information from all the departments, uh we can create a much better experience. And instead of just doing analytics and telling you what is happening, we use the deep context to tell you why things are occurring and what you need to do about it.

Moving Beyond KPIs To Outcomes

SPEAKER_01 0:52

Brilliant. So as an early stage startup, uh you have an MVP, you have an initial offer. Maybe describe what you're offering today and kind of what direction it's going in.

SPEAKER_00 1:01

Sure, yeah. So uh so quite a bit has changed, obviously, in the last year. We're well past uh MVP. We've we've got 35, 40 deployments just in the last year uh uh alone. And so uh customers are finding us for uh several use cases, and and the primary is getting past the basic KPIs that you would have in a contact center. So beyond service level, beyond QA, beyond CSAT, and get into the deep meaning of what's going on. So uh what is driving success? Who are my best agents and what is the DNA of them, and how can I apply that both to my human talent as well as it use that to accelerate my internal AI initiatives? And so it's the feedback mechanism to go a lot deeper to actually create outcomes rather than just telling you what's going on.

A Real Root-Cause Success Story

SPEAKER_01 1:42

Interesting. Do you want to talk about a favorite customer? I don't want to pick favorite children, but yeah, and how they're using the platform in their day-to-day.

SPEAKER_00 1:50

Yeah, yeah. There's a few examples, but one of the one of the best stories was a uh apparel brand. Uh, they have uh a shoe product line, and there were a number of customers calling in saying, I have I have an issue with with the product, there might be a defect if it's wearing a little bit faster. And so the typical information that we would see in the contact center is who they are, and then that they're reporting a problem on a shoe. But we tied that data into uh the ERP data, the sales data in the back end, and we determined specifically what shoe that person purchased, when it was, what lot number that came from. Wow, right, and and tracked it all the way back to the supply chain to figure out where the root causes were, then use that information also to proactively reach out uh to customers and get ahead of an issue instead of having to be reactive.

Deploying Across Legacy Tech Stacks

SPEAKER_01 2:35

That's fantastic. And how do you deploy in a multi-vendor environment lots of legacy tech? That's our bread and butter. Um what does that look like?

SPEAKER_00 2:42

Yeah. So we've created a uh a data system that allows us to essentially data lake the information. We correlate uh the information by using a lot of uh just different proprietary techniques that we've built uh to take the noise uh out and we call that signals. So we create hundreds and hundreds of signals per customer. Some of them are a little more kind of broader, broader industry spoke uh focused, but the system actually learns by listening to the phone calls and looking at the related data and it extracts new information and then provides the customer with insights not only on the things that they know to look for, but the trends and patterns that they they they don't know about. And then we we come up with plans to make change and measure it.

Standing Out In The Agentic AI Wave

SPEAKER_01 3:22

So onwards and upwards, what's next? You're growing the team, you're growing the portfolio. How do you go to market with uh as a startup these days?

SPEAKER_00 3:30

Well, it's an interesting interesting time, right? Um what we what we've noticed is that there's a number of uh agentic AI companies, and that's a really good thing. Just a few, yeah. Yeah, yeah, yeah. So it's it's hard to stand out from a marketing perspective. But our our goal is to take a company to go a lot deeper into using the information they have on their relationship with a customer and say, how do I truly make an impact rather than just trying to solve the problem of the contact center island, right? So uh focus on on the back office uh you know side of it, growth initiatives, marketing and initiatives. An example would be alerting, hey, you've you you you put out an initiative, we're getting a lot of calls about it. Here's what's working, here's what upsells are working, here's what you know, here's the training that we need. Uh, as we see AI take on uh more and more, we we become the feedback mechanism for that, allowing customers to deeply focus on on the changes and then getting it at measuring the effectiveness and quickly adjusting. So rather than looking at it a month after the fact, looking at it in real time and and making an impact.

New Markets Plus How To Connect

SPEAKER_01 4:29

Great. So what's uh what are you excited about this year as we head into Q2, Q3? Yes. Uh what's on your mind?

SPEAKER_00 4:34

Well, we've got a steep ramp up uh quite a bit. Uh so uh we're the we have some really interesting um customers that we're working with that are that are outside of the what we traditionally think of as the contact center. Uh for instance, some 211 companies, and we're able to make an impact on matching people to homeless shelters and things like that, right? It's the same technical foundation. And what we found is that our signals architecture allows us to help companies think about it, use contact center capabilities and technologies, but across the whole organization. So we're very focused there. Uh, we're also focused on you know helping the ecosystem that's traditionally within the contact center uh to leverage and actually see successes in their AI deployments.

SPEAKER_01 5:14

That's fantastic. And how can folks engage with you? I assume you're willing to partner, you're willing to work with direct with enterprises. Yes. They can reach out to your website.

SPEAKER_00 5:23

Is that yeah, website's easy spearfish.ai. Uh also on LinkedIn, uh Ray Bohack or uh at spearfish AI.

SPEAKER_01 5:30

Fantastic. Well, congratulations. It's great to see new blood, new innovation, new ideas in this space with a lot of legacy companies. So you're well done. Yeah, thank you.

SPEAKER_00 5:39

Appreciate it. It's it's an exciting time.

SPEAKER_01 5:41

Have a have a great week.