How Canbnb Built a High-Performing Support Team Using AI
In the early days, Jo’s morning routine was simple. Running a lean operation at Canbnb meant she handled all guest communications herself, responding to emails and messages while juggling last-minute bookings. Two freelance cleaners managed turnovers, and when things got busy, even the owner pitched in to clean properties.
It wasn’t perfect, but it worked.
Then, growth hit.
From 7 properties to 170, the pace was relentless. What had once been a manageable workflow quickly turned into a daily scramble to keep up. Guest messages overflowed, on-site teams struggled to stay aligned with the growing virtual support staff, and small inefficiencies began compounding into operational bottlenecks.
The Challenge
One morning, Jo logged in to find 630 unread messages—some from guests, some from cleaners, and a few urgent ones from owners. By the time she triaged the inbox, a check-in issue had already escalated into a full refund request. “We were moving too slow,” she recalled. “And at that scale, slow is expensive.”
Logging into multiple platforms, cross-referencing guest requests with cleaner schedules, answering urgent owner inquiries, all while making sure nothing slipped through the cracks, Jo’s morning routine was no longer no longer sustainable.
The stress of managing scale without the right infrastructure was mounting. Canbnb needed a system that could keep up with their growth—without breaking their operations.
“We couldn’t run things the same way anymore,” Jo recalls. “The volume of messages and tasks was overwhelming, and the disconnect between virtual and on-site teams was creating inefficiencies we couldn’t ignore.”
Their operational challenges boiled down to three key problems:
- Virtual vs. On-Site Coordination – Remote support staff and on-the-ground teams needed to work in sync, but managing that balance at scale became increasingly difficult.
- Response Time and Guest Experience – With more properties came more inquiries. Slow response times meant unhappy guests, and scattered systems made it harder to track urgent issues.
- Onboarding Complexity – Property management software is notoriously difficult to implement at scale. With 170+ properties, switching systems felt like a high-risk, high-friction move.
Jo and Dan, the company’s leadership team, knew they needed a better solution—but they weren’t convinced AI was the answer.
The Skepticism
The buzz around AI in hospitality was everywhere, but Jo remained skeptical.
“I’m in operations every day. I see the gaps in these systems. AI sounded promising, but I wasn’t convinced it could really fit into our workflow.”
Dan, however, saw the bigger picture. As Canbnb pushed toward their next growth milestone, he knew they needed a platform that could do more than just streamline messaging. It had to be their central system—the foundation for everything from guest interactions to team coordination.
Their biggest hesitation? Onboarding. Property management systems are notoriously difficult to migrate, and the last thing they wanted was a drawn-out, complicated transition.
But when they set up HostAI, their doubts quickly disappeared.
The Shift
“Honestly, setting up HostAI was one of the easiest things I’ve ever done,” Jo admits. "Compared to other property management platforms, which often require weeks (or even months) to fully integrate, HostAI was up and running in a fraction of the time.”
More than just ease of use, it was that it fit into their existing operations:
- A structured inbox made it easier to monitor guest inquiries and escalate urgent issues before they became problems.
- Multi-Channel Integration – HostAI connected seamlessly with Hostaway, WhatsApp, Email, SMS, and a Chat Widget, consolidating all interactions into a single interface.
- Dedicated Inboxes – Canbnb structured their team’s workflow with separate Guest, Owner, and Vendor inboxes, ensuring the right teams handled the right conversations.
- AI as the voice & tone guide – Instead of training each new hire manually, HostAI enforced brand-aligned responses and company policies automatically.
The Transformation
Once onboarded, Jo saw a shift in her team’s mindset.
“We’re no longer just answering messages—we’re editing and guiding our AI assistant. The cognitive load has dropped, and each guest services rep is 10x more impactful.”
More importantly:
- Automating at Scale – HostAI now helps Canbnb send roughly 1,500 messages per week, with 60% handled by AI.
- Operations became streamlined – No more scattered attention across platforms. Remote agents could see exactly what on-site teams needed in real time.
- Guest interactions improved – AI-assisted replies ensured that every guest received timely, accurate responses, even during peak hours.
- Company policies were reinforced – AI suggestions kept human agents aligned with company standards, reducing errors and inconsistencies.
- Better visibility into guest issues – HostAI’s built-in reporting helped them track the most common guest concerns, allowing them to address root causes proactively.
One of the biggest wins? The ability to track and act on guest feedback more effectively. HostAI’s review dashboard gave them a real-time pulse on guest satisfaction, allowing them to marry guest reviews with cleaner performance and reservation data.
HostAI didn’t just improve efficiency—it became the connective tissue between their virtual and on-site teams.
The Outcome
Today, Canbnb isn’t just using HostAI—they’re building their future on it.
“We see HostAI as our central platform,” Dan says. "As we push past 200 properties, it’s not just about keeping up—it’s about scaling the right way, without losing control of our operations.”
With AI reducing friction, streamlining communication, and reinforcing company standards, Canbnb is moving toward its next phase of growth with clarity, not chaos.
And as for Jo? The morning routine looks a little different now.
“It’s just…easier,” she says. “Everything is right where we need it. We’re not scrambling anymore. We’re in control.”
