High-value medical device OEMs are facing a paradox: service performance matters more than ever, yet the cost of delivering it continues to climb.
The result is familiar:
At the upcoming Field Service Medica 2026 event, we’ll be talking about how manufacturers can move beyond reactive service operations to autonomous service journeys.
Complex devices, highly regulated environments, and distributed field service models create layers of friction:
These aren’t isolated inefficiencies; they’re decision gaps hidden in your current processes. And until you map them out, they continue to drain margins.
Before you can remove service pain, you need to see it clearly.
The R: Review the current process step of our TRACK framework is where organizations uncover the true sources of friction and cost. This step focuses on understanding how work actually happens today.
This review looks at:
In other words, this is where the pain lives.
Once those pain points are visible and measurable, the conversation shifts from “we need more people” to “we need better decisions.” That’s where Service AI workers come in, not as helpers, but as painkillers.
Circuitry.ai Service AI workers act as an intelligent layer across your existing service systems, enabling autonomous decisions without replacing your technology stack. They are purpose-built for manufacturers and designed around real service, parts, and warranty workflows.
Each Service AI worker plays a distinct role in eliminating service pain.
The Service Advisor acts as the diagnostic layer of the journey.
By ensuring decisions are based on complete context, the Service Advisor removes one of the biggest sources of pain: wrong decisions made early.
Why it matters: A device with complex warranty conditions or regulatory compliance requirements should never be misdiagnosed due to incomplete context.
AI Agents handle the execution layer: the work that often slows teams down.
This is where service teams feel immediate relief. Work moves forward without waiting, chasing, or re-entering data.
Why it matters: Parts logistics, traceability, and cross-system updates are often manual, and every manual step is a margin leak.
Pain relief only matters if it lasts. The AI Analyst ensures that outcomes improve over time by:
Instead of relying on anecdotes, teams can see clearly and continuously whether first-time fix rates, resolution times, and cost per case are improving.
Why it matters: You can’t improve what you can’t measure. The AI Analyst validates that decisions improved uptime, reduced unnecessary work, and lowered cost.
The value of this approach is measurable. After a disciplined review reveals where service pain lives, Service AI workers deliver relief in ways that:
Organizations move from reacting to problems to preventing them, and from absorbing cost to recovering value.
Service pain doesn’t always announce itself. It hides in dark data, inconsistent decisions, and processes no one has mapped end-to-end.
That’s why many organizations begin their Autonomous Service Journey with the Review step of the TRACK framework. It brings clarity to where value is leaking today, and where AI workers can deliver immediate relief. You can schedule a margin recovery audit to identify key pain points and how we can help.
Because the fastest way to improve service outcomes isn’t working harder. It’s seeing the pain clearly and applying the right painkiller.
If you’re attending Field Service Medical, we’d love to connect and talk through:
Here’s where you can engage with the Circuitry.ai team at the event.
In this session, Ashok Kartham, CEO of Circuitry.ai, is joined by Brent Lloyd, VP, Service and Technology Operations at Noah Medical, to discuss how AI-driven Service Decision Intelligence gives support teams immediate access to accurate, compliant answers within their existing workflows, so they can reduce friction and accelerate resolution times.
Sit down one-on-one with our expert team to explore how Service AI workers can be applied to transform technical support and field service, boosting productivity, improving service outcomes, and reducing cost-to-serve in regulated medical device environments.
Join an interactive roundtable to identify and reduce operational waste that erodes service margins. You’ll explore practical ways medical device service teams are reducing waste and improving first-time fix rates without adding headcount. Led by Josh Russell, VP of Products, Circuitry.ai, and Eduardo Bonefont, Strategic Advisor, Predictive Alerts.
Or stop by Booth 208 anytime to chat with us, schedule a demo, and explore how our Service AI workers can improve your service outcomes.