How Dynamic Quest Replaced Email Ping-Pong with a Conversational AI Service Desk

Dynamic Quest is an MSP running a roughly 50-person service desk spanning Tier 1, 2, and 3 support alongside a dedicated platform and operations tools team. Its client base includes organizations across multiple industries, among them credit unions and other clients with strict uptime and compliance needs.

As the company grew, its leadership team recognized that clients weren't going to tell them what better support looked like. It was up to Dynamic Quest to figure that out.

"It was up to us to say, okay, how can we provide a better experience?" — Natalie Makowka, VP of Technology and Operations, Dynamic Quest

Before Thread, most of Dynamic Quest's support requests arrived through two channels, and neither gave technicians much to work with. About 70% of tickets came in by email, where a client might write in with something as vague as "I'm having trouble" and leave the team guessing. The remaining 30% came by phone, constrained by a static IVR that couldn't be reconfigured on the fly and often sent clients straight to "representative" instead of the right team.

The Core Problem: Client requests were arriving through slow, low-context channels, and technicians had almost no shot at resolving anything on the first contact.

"You have almost zero opportunity at a first contact resolution with that client, because just to even understand where their problem is stemming from, you're probably looking at multiple emails over multiple days." — Natalie Makowka, VP of Technology and Operations, Dynamic Quest

The operational friction showed up in a few specific ways:

• About 70% of tickets arrived via email, each requiring multiple rounds of back-and-forth before a technician understood the actual issue
• The other 30% came by phone, limited by IVR routing that couldn't flex to match how clients were actually calling in
• An earlier attempt at a different AI chat vendor stalled out when it turned out to rely on manually fed documents in a format that didn't match the team's IT Glue knowledge base, with no integration path forward
• Client sentiment reflected the strain: Dynamic Quest's NPS was negative in the years before Thread

A cold call from Thread's team, taken right as Dynamic Quest was reassessing its chat strategy after the earlier vendor fell through, opened the door to a different approach.

Thread was deployed as Dynamic Quest's AI service desk layer, connecting Microsoft Teams to Autotask and automating ticket categorization, prioritization, and structured intake.

Natalie and her colleague Marie ran the implementation themselves, without pulling in a software development team. Thread's onboarding walked them through the setup step by step, starting with a set of pre-built, common-to-every-MSP intents that let them launch with real functionality on day one instead of building from a blank slate.

"You have steps. So you meet with your client success manager, they're like, okay, today we're going to set up these things, here's your homework. You click the button. When your homework is done, you get confetti." — Natalie Makowka, VP of Technology and Operations, Dynamic Quest

From there, the team layered in Dynamic Quest-specific logic: automatic severity escalation for credit union clients when core financial systems were affected, and automatic priority bumps whenever a ticket touched a flagged VIP user in Autotask.

Today, Thread's triage agent (which the team nicknamed "Questy") reads and categorizes tickets automatically, a job that used to fall to a dispatcher manually applying Autotask speed codes one ticket at a time. Technicians receive requests that are already prioritized and routed, rather than waiting on a person to work through a queue by hand.

The rollout followed a deliberate alpha-to-beta structure. Dynamic Quest's internal IT team tested the Teams integration first, surfacing the kind of rough edges only an internal team would catch. Once that was stable, the company brought in its ten-client advisory board as the next test group before expanding to the full client base.

"If we were the alpha, then they were the beta." — Natalie Makowka, VP of Technology and Operations, Dynamic Quest

That structure let the team keep refining the agent as real conversations came in, adjusting tone, correcting missteps, and tightening the intents Questy used to triage and reassure clients before a ticket ever reached a technician.

Day in the Life

A credit union client's end user opens a Teams chat to report a system issue. Thread's triage agent asks three quick questions: where they're located, what they were doing, and how long the issue has been happening. It offers a short reassurance that the team is already aware and working on it, then merges the conversation into the master incident ticket already open in Autotask. Natalie and Marie watch the incident ticket fill in with detail from every affected user in real time, using it to pinpoint an intermittent problem across roughly 350 end users faster than they could have if each person had emailed in separately.

Dynamic Quest Rebuilt Client Trust and Cut Ticket Friction

Client sentiment tells the clearest story. Dynamic Quest's NPS moved from negative to 45 in its most recent survey, a shift Natalie attributes in large part to the structured, faster intake Thread introduced.

"Our last survey, we were at a 45 [NPS]. That's kind of through the roof for an MSP." — Natalie Makowka, VP of Technology and Operations, Dynamic Quest

Chat adoption has grown from zero to about 30% of all tickets company-wide, and to roughly 70% among Dynamic Quest's top-tier "Level 1" clients. That adoption tracks directly with resolution speed: clients who lean on chat see first-contact resolution above 60 to 65%, compared with 50 to 60% for clients still relying mostly on email and phone.

Did Thread improve first-contact resolution? Yes. Clients using chat as their primary channel see first-contact resolution rates of 60 to 65%+, compared with 50 to 60% for clients who haven't adopted it as heavily.

Did Thread reduce manual work for technicians? Yes. Auto-categorization and prioritization now happen automatically, including custom rules for VIP accounts and credit union severity that previously depended on a dispatcher manually applying the right Autotask speed code.

Dynamic Quest set out to give clients a way to reach support that matched how they already communicate, instead of forcing them through email threads or phone queues that couldn't flex to match demand. Thread gave the team a channel they could stand up quickly, without a development team, and then shape to their own operational rules as they learned what their clients actually needed. The result shows up where it matters most: clients get faster, clearer help, technicians spend less time on manual triage, and a company that once measured negative client sentiment now points to an NPS score its own leadership calls "through the roof for an MSP."

Takeaway: Dynamic Quest shows that MSPs using Autotask can move from reactive, low-context ticket intake to a structured, conversational service desk by deploying Thread as their AI layer, without replacing their PSA or requiring a dedicated development team to configure it.