How DaySmart unified nine brands onto one AI-first support system

DaySmart builds business management software for the companies behind everyday services, from salons and veterinary practices to recreation programs, sports leagues, and payments. In just a few years, acquisition turned DaySmart from a three-brand company into a nine-brand portfolio.

For Angel Horowitz, Director of Customer Education and Enablement at DaySmart, growth created a new kind of challenge. “As we acquired more companies, we acquired their tech stacks too,” Angel says. “We were using around five different systems, which made it difficult to train new support people, standardize how teams worked, and pull reporting that lined up across the business.”

DaySmart needed one operating layer for every brand it had acquired, and every brand still to come. So the team decided to consolidate support, help content, and customer communication into a single platform, moving all nine products onto Intercom in four months. Once that foundation was in place, DaySmart brought in Fin, an AI customer agent, to scale customer service.

Today, Fin resolves 72% of the conversations it touches, handles more than 10,000 resolutions a month, and automates 38% of total support volume.

The result is a new operating model and better work. Fin handles the front line, while DaySmart’s people move toward proactive success, customer education, onboarding, and business consulting.

Here’s how DaySmart got there.

Years of acquisition turned DaySmart into a broad product portfolio serving customers across very different industries. DaySmart Salon helps salons manage bookings and payments. Dash helps recreation facilities run registrations, leagues, schedules, and payments. Time To Pet supports pet-care providers with scheduling, invoicing, and client communication.

Each product is also highly configurable around how each customer runs their business, from the services they offer to the workflows their teams follow. That makes the software more flexible, but it also makes support more nuanced. “Because our systems are so customizable, we’re often acting more like business consultants than a traditional support team,” Angel says.

As DaySmart acquired more companies, it also inherited their support infrastructure. The CS team was working across a fragmented tech stack, with support conversations, customer messages, announcements, and reporting spread across five different tools. Training was harder, workflows were difficult to standardize, and reporting meant stitching together data from systems that did not always line up, making the full picture hard to trust.

It created friction for customers too. “We had very long wait times,” Angel says. “For some products, we were more of a call center. We had fixed support hours, and outside those hours, the help center was really the only option. Customers couldn’t chat with us and get answers in the moment, so if they were setting something up on a weekend, they often had to wait until Monday.”

DaySmart decided to unify support on Intercom to get off the inherited stack and build a single service model for their next stage of growth. “The tools in our old tech stack weren’t intuitive, and they were far behind with getting into the AI game,” Angel says. “We knew it was worth moving to a system that was easier to use, better for our customers, and ready for the AI we wanted to build into support.”

“One of our products had actually been on Intercom before, so we already had people in the company who’d used it and talked about how amazing it was. That made the decision to switch a lot easier,” Angel recalls.

DaySmart ran the change in two deliberate moves.

Migrating nine products to one helpdesk

For DaySmart, moving to Intercom was a major migration. Each product had its own customers, support workflows, help content, and communication needs. All nine had to move into one system while support kept running across the business.

The Fin team partnered closely with DaySmart through the move, working with teams across support, marketing, product, and leadership to validate the setup, build the business case, and prepare each team for the migration.

“We migrated nine products in about four months,” Angel says. “Intercom is plug and play in a lot of ways, which made the migration much easier than it would have been with another system.”

Adding Fin to the front line

With the helpdesk in place, DaySmart turned to the second problem: coverage. Customers still needed help outside the hours and volume levels a human team could realistically support, so the team decided to implement Fin.

The rollout was gradual. The CS leaders knew customers were still cautious about AI, so the team started where the gap was clearest: after-hours and weekend support. The AI agent could add coverage when human support was already unavailable, without changing the experience customers expected during business hours.

At the same time, DaySmart was rebuilding its help content so Fin had better answers to work from. “AI is only as good as the content that powers it,” Angel says. As the content improved and Fin proved itself in real conversations, DaySmart expanded it into business hours, then brought it into email.

That gave DaySmart a playbook for every new acquisition. The team already knew how to adopt AI; the speed of each rollout now depended on the strength of the content behind it. “The brands with the cleanest content moved fastest,” Angel says. “That’s why a newer acquisition like Time To Pet, which already had strong, up-to-date help content, could launch with Fin on the front line from day one and see high resolution rates almost immediately.”

Today, Fin is the front-line AI Agent across DaySmart’s brands, while teams across all nine brands work from one service system. Customers are no longer moving through disconnected support paths, and the team can see every conversation in one place, whether Fin resolved it or a human teammate stepped in.

Fin now resolves 72% of the conversations it touches across email and chat, driving more than 10,000 resolutions a month. It performs even better for brands with strong knowledge bases, where Fin is set as the front line from day one. “We were skeptical at first, like everyone is with AI,” Angel recalls. “But Fin has been unbelievable. For our fully AI-first brands, we’re at about 90% involvement and a 75% deflection rate.”

For DaySmart, those numbers translate into coverage the business could not efficiently build with people alone. Customers can now get help instantly whenever they reach out. “The biggest value that Fin has provided for us is being able to provide support 24/7 to our customers, without us having to staff it that way,” Angel says. “Having humans available around the clock simply isn't efficient, so being able to leverage Fin for that has made a huge difference for us.”

With strong early results, Angel’s focus shifted from proving Fin could work to improving how their support model operated. Running support across nine brands means nine sets of customers, content, and workflows to manage. Angel and the CS Leaders needed a way to monitor how Fin and the support team were performing, without manually reviewing thousands of conversations.

Fin gives the team visibility they never had before. In the old stack, reporting meant piecing together numbers from tools that rarely agreed. Now, they can see what customers are asking, where they run into issues, and where content needs to improve across every brand.

With Monitors, the team can keep quality high as each brand moves further into AI-first support, giving the team a way to review accuracy and catch issues before expanding coverage.

Then Fin Operator, an agent for customer operations, turns that visibility into action. Angel describes the outcome she wants in plain language, and Operator configures Fin for her. “Fin Operator has been life changing,” Angel says. “Work that used to take us an hour or more now takes 15 or 20 minutes. It helps us streamline how we build Fin guidance and manage different parts of the system, which is important as we start connecting more data and preparing Fin to handle more complex issues.”

The new support model gave the CS Leaders room to rethink the work inside DaySmart. “The goal has never been to replace people,” Angel says. “The goal is to leverage AI so people can do their jobs more efficiently.” With AI freeing up team capacity, Angel was able to create new roles and the CS Leaders were able to shift their teams toward higher-value customer work. DaySmart built a CX Education department and moved more of the team’s focus into customer education, success, and consultative onboarding. For a business with highly configurable products, that means people can spend more time helping customers shape the software around how they actually run their business.

“Since we’ve started leveraging AI, it’s been amazing to see the different departments we’ve been able to create,” Angel says. “Before, support roles were mostly reactive. Now they’re more support and success roles, and we can be more proactive.”

For Angel, this is the point of AI: it changes where people create value. Fin keeps the front line moving, while human agents focus on the work where judgment, education, and customer partnership matter most.

DaySmart now has one support model that scales across every brand it owns and every brand it acquires, without losing the flexibility each one needs.

The next phase is making Fin more capable across the full customer experience. By connecting Fin to more data in DaySmart’s systems, the team is preparing it to resolve more complex work, including invoice questions, configuration issues, and operational requests that still need a human today. “A year ago, AI still felt like a buzzword,” Angel shares. "Today it's how we operate, and we're still finding new ways to use it."

And as Fin takes on more of that work, DaySmart’s people can move closer to the moments where human judgment matters most. "Don't be afraid of AI," Angel says. "It's a scary time for some people who think AI is going to take jobs away from their teams. But it's really supposed to be a tool that makes your teams more efficient. So lean into it, figure out how to make it work, and explore all the options."