How Asymbl Turned ZoomInfo MCP Signal Data Into Always‑On Pipeline
Original case study publication date is 9.23.26
Asymbl is a Workforce Orchestration Company™ based in Austin, Texas, that helps staffing and recruiting firms bring people, AI, and software together as one hybrid workforce. They create the software, put the AI to work, and have the consulting expertise to orchestrate it all including:
Software that helps supply talent by finding and hiring people with predictability, cost efficiency, and speed.
An AI & Digital Labor practice that guides firms on how to know where AI belongs, where it doesn't, and how to make it pay off, including digital workers who are either pre-built to work inside of their software or custom built.
A Salesforce and Anthropic consulting and implementation practice that designs solutions, and builds the systems of work then integrates the data underneath it all.
Founded a little over three and a half years ago, Asymbl has grown fast, and its own go-to-market team is a blend of people, AI agents, and digital workers. One of those workers is Teddy, a Digital Sales Development Representative, who works inside Asymbl's Salesforce instance and Slack environment, sending outbound messaging and nurturing inbound leads around the clock.
But Teddy, and the broader digital workforce Asymbl has built alongside him, are only as good as the information they're given. That is where the company's partnership with ZoomInfo enters the story.
"It's like a cheat code. It's honestly like a cheat code."
Greg Symons, Co-Founder and President, Asymbl
Flying Blind, or at Least With One Eye Shut
Before ZoomInfo, Asymbl was not without data. The company pulled information together from webinars, conferences, web content, and relationships. But Greg Symons, Asymbl's Co-Founder and President, is candid about what that approach could and could not accomplish. "I don't want to say we were in the stone ages," he says. "But the reality is you're flying blind, or at least with one eye shut."
The core problem was scale and precision. "There's a huge population of people that exist," Symons says. "It's physically impossible for us to be able to touch all the right people at the right times." Asymbl's account executives were focused on named target accounts, but that list represents only a fraction of the company's full ideal customer profile (ICP), and there was no efficient way to know when the right person, at the right company, was showing real interest.
That same data problem, Symons argues, extends well beyond Asymbl's own sales motion and into the broader AI conversation. "It's very rare that we engage with a prospect or a customer who's like; our data's great," he says. "If you have outdated information, it doesn't matter if your system is wired through an LLM. You really need to be able to use that information to make more informed decisions." Without a solid data foundation, he warns, companies chase the excitement of AI without the structure to make it pay off, and the costs can pile up fast. Closing that gap between ambition and infrastructure is one of the places ZoomInfo is helping Asymbl.
Signals That Let Humans and Digital Workers Both Move Faster
Asymbl brought ZoomInfo into its stack to feed signal data into Salesforce and Slack, two places Symons says where a lot of work gets done inside the company. "A lot of our digital workers are living in our Slack workspace."
The signals ZoomInfo surfaces now drive two parallel paths. For named target accounts, prioritized by Asymbl's ICP, signals on known or unknown contacts flow into Salesforce and alert account executives when a meaningful action is worth taking, whether that is a phone call, an email, or a handoff to a human BDR. For the much larger population of companies that fit Asymbl's ICP but are not on the named target list, those signals feed Teddy, who nurtures the lead until his primary KPI, a scheduled meeting for a human, is met.
Central to that second path is ZoomInfo's MCP, which Asymbl has adopted to connect signal data into the tools its people and digital workers already use, without the overhead of building and maintaining point-to-point API integrations. "MCPs are far more flexible for us," Symons says. "It allows us to curate the information and surface it where it should be exposed and how it should be exposed in a much, much more flexible way."
Whether the MCP is called inside Salesforce to drive top-of-funnel acquisition, inside Slack to help qualify an opportunity, or inside the company's Anthropic Claude environment to hydrate a customer presentation with more deterministic information, the goal is the same. "It's one tool that has surfaced in different places to solve different jobs," Symons says, "based on the type of work that people are doing."
The payoff, Symons says, is a better experience on both sides of the conversation. "It's always refreshing to get some type of meaningful information that resonates with the problems you're trying to solve with a partner who's an expert in the area," he says. "ZoomInfo helps us hone in on the right signals to take action that is going to produce higher output for our organization."
Meeting Bookings Nearly Double Since Adopting ZoomInfo MCP Signals
The clearest evidence of that impact shows up in Teddy's numbers. "We've actually seen his meeting bookings almost double from pre-MCP ZoomInfo signals," Symons says. Notably, that gain came without retraining Teddy on new company knowledge. "We haven't necessarily changed his knowledge. He's still trained on what the company does. But his ability to engage and leverage the signals and enrich the information that he has available to him has just about doubled his meeting booking conversion rate, which is incredible."
Asymbl's human BDRs are seeing a similar lift. The company has recorded a higher conversion rate on initial conversations and meetings set by its account executives, driven by the same prioritization signals now guiding outreach. Perhaps most striking, Asymbl has started generating what Symons calls "grassroots opportunities" from companies that fit its ICP but sit outside its named target account list, a population Symons describes as running into the thousands of companies and contacts that would otherwise be nearly impossible to canvas efficiently. "We're even starting to see, I would say, grassroots opportunities be created as a function of these signals," he says. "It has actually started to generate new business opportunities for us that are in the pipeline right now, which is amazing."
Asked whether that was unexpected, Symons is precise. "I wouldn't say that it was inherently unexpected," he says. "I think for me personally, what's unexpected is how quickly we were able to start to see positive deal flow through that channel."
A Flexible Foundation for What Comes Next
For Symons, the real differentiator is how little friction stands between having an idea and acting on it. "For us, we deeply understand the outcomes that we're looking for, and we're able to structure those outcomes using ZoomInfo very easily to ultimately deliver on what we need to deliver on as an organization," he says. He compares it to a shared set of tools available to everyone, where the difference lies in how effectively they are used. "Everybody has access to paper and words. How you put those words together to tell a story is something that's very unique to the individual," he says. With ZoomInfo, that means Asymbl can adjust its signals and strategy as the market shifts without losing momentum. "It's a very flexible and fluid and powerful application for us."
As Asymbl continues to scale its hybrid workforce, Symons sees the ZoomInfo partnership as foundational to a philosophy the company has held since its earliest AI experiments: that technology is the easy part, and the real work is building a mindset, and a data foundation, that can keep pace with it. "We are not an AI company," he says, "and it would be very difficult for us to build and strategize and execute on a plan if we had a different relationship with what and how we think about AI." With ZoomInfo's signals and MCP feeding both Teddy and his human colleagues, Asymbl has built exactly that relationship, one qualified signal at a time.
