MSPs track email, chat, and ticket activity carefully. Phone calls, however, are rarely measured. Some of the most valuable client service information never gets captured.
Filling that gap presents a major opportunity, according to Mark Alayev, co-founder and chief magic officer of Thread.
“All of those amazing calls that are happening with the service desk, they’re discussing the nuances of service delivery. They’re doing a restructure, opening a new office, or hiring a new person. All of that detail, but nothing’s being reported; nothing’s transcribed. And it represents 40% of all overall service volume.”
That realization led Alayev and Co-founder Matt Linn to create Thread Voice AI. Thread’s new platform captures those conversations and turns them into actionable service intelligence. For MSPs, that can mean faster response times, stronger customer satisfaction, and the ability to scale operations without adding headcount.
Replacing Voicemail with Intelligent Intake
Thread initially built its platform around chat communications. That work produced a conversational dataset that helped train the company’s AI models. Expanding into voice became the next logical step.
One of the first ways MSPs are harnessing Voice AI is to replace traditional voicemail systems.
Support calls often come in waves, spiking at predictable times of day. When technicians are busy, those calls typically route to voicemail. Someone later listens to the recording, creates or updates a ticket, assigns a priority, and routes the issue to the right technician. However, that manual process can delay response times and leave critical issues unnoticed.
Mark Alayev
Thread’s AI agent gathers caller information automatically and creates a ticket in real time.
“[Clients are] already talking to an AI, but our Voice AI has the ability to automatically detect if that person exists in their ticketing system,” Alayev told ChannelPro. “If we can match it by number, it will ask their name, their company name, and what’s going on. Then, it will automatically prioritize it and route it back to the service desk.”
The system can also detect urgent issues after hours, helping MSPs identify critical incidents even when no technicians are available to answer calls. For MSPs, faster visibility is critical when dealing with high-priority incidents.
Helping Technicians Resolve Issues Faster
Voice AI also supports technicians during live calls. The system can listen in real time and surface relevant details about the caller, including previous incidents or configuration issues.
That context can significantly reduce troubleshooting time. “Instead of spending 15 minutes looking up that person’s profile, now, within 90 to 120 seconds, the technician is getting the information they need to resolve the issue faster,” Alayev said.
For service providers, those efficiency gains translate directly into stronger performance metrics. The most important is time to resolution, Alayev stressed. Faster resolution times improve customer satisfaction and retention, which directly impact MSP profitability, he added.
“That’s the big one. Imagine you have an IT problem. You want to get it out of your way so you can actually do your job.”
A gradual AI adoption model for MSPs
Thread positions Voice AI as a phased rollout rather than an all-at-once shift.
Scaling Service Without Hiring More Staff
Voice AI can also help MSPs grow without expanding headcount.
Thread designed the platform to work with virtually any phone network. AI agents function like additional service desk staff. Each agent has its own phone number and can gather details before transferring the call to a technician.
The approach allows MSPs to handle higher service volumes while keeping staffing levels stable. “Our hypothesis is that the world will have so many more businesses now because it’s so much easier to set up businesses,” Alayev explained. “So yes, our goal is to grow revenue per employee without increasing headcount, not to displace existing workers.”
For MSPs facing talent shortages or rapid growth, that efficiency can translate into higher revenue per employee.
Building a Knowledge Base from Every Conversation
Another advantage of Voice AI is the intelligence it builds over time. Thread’s platform analyzes interactions across chat, email, and voice channels. The system then learns from those conversations. It creates a memory of users, environments, and recurring issues to improve future support interactions.
“When you call and say, ‘I need a new dock for my new computer,’ the Voice AI will respond, ‘I see that you recently got a new MacBook Pro M5. Are you asking for a dock for that?’ That experience is incredible.”
Over time, that growing knowledge base can reduce troubleshooting time and make service more proactive.
Preparing MSP Teams for an AI-assisted Future
The next frontier for Thread Voice AI is outbound calls. This is when the AI can make the call, or when the human can make an AI-assisted call to the end user.
As AI becomes more embedded in service delivery, technicians’ roles also will evolve. Instead of handling every task themselves, they may oversee teams of AI agents that assist with intake, documentation, and troubleshooting support.
“In the world of the future, you may spend a year working. Then, you’re going to be able to manage and supervise your own little team of AI agents,” Alayev illustrated. “The skills that future technicians are going to need to learn is how to manage AI agent much earlier than they do when they’re managing their human agent counterparts.”
For MSPs, tools like Voice AI could mark a shift toward more scalable service models. Automation handles routine tasks and technicians focus on higher-value work.
Anjali Fluker is managing editor for The ChannelPro Network, where she covers news, trends, and best practices for the MSP community. She specializes in telling the stories that matter to IT providers serving the SMB market. When she’s not reporting on the latest in managed services, she’s connecting with channel pros at industry events across the country.
Images: Thread
