Beyond Diagnostics: How SynqRail Helps Auto Repair Businesses Manage the Growing Complexity of Insurance Repairs
Sept. 4 2026, Updated 3:16 p.m. ET
U.S. auto repair businesses are handling fewer insurance repair claims today, yet spending more time on each one. The reason goes beyond the cost of parts or the severity of vehicle damage. Modern repairs increasingly involve electronic system diagnostics and subsequent calibrations, additional insurer approvals, parts orders, and document exchanges. As a result, a vehicle may be technically ready for the next stage of repair but remain at the shop because an approval is still pending, a part has not arrived, or the next decision has not been made in time.
That shift is reflected in data from CCC Intelligent Solutions. In its Crash Course 2026 report, the company describes a changing mix of U.S. auto insurance claims: as insurance premiums, deductibles, and overall vehicle ownership costs rise, consumers are increasingly paying for minor damage out of pocket. The result is a greater concentration of higher-severity claims reaching insurers. In 2025, the share of claims in which vehicles were flagged as total losses reached a record 23.1%, while calibrations appeared in 28.3% of repairable estimates.
For the U.S. auto repair industry, a more complex insurance claim creates more points at which work can stall: approvals, supplemental estimates, documentation, parts, and calibrations.
Oleksandr Moskalchukhas focused on this problem while developing SynqRail, an AI platform. As the owner of Easy Fix Auto Body, he approaches insurance repair from the perspective of a business where a delay in an approval, a parts delivery, or the next operation can affect the timeline of the entire repair order. His central question is straightforward: How many days is a vehicle actually being repaired, and how many does it spend waiting for the next action?
“I look at it pretty simply: if no one is working on the car right now, I want to know why. SynqRail shows where the process has stopped and what needs to happen to get it moving again. In the end, we’re not shortening the repair itself. We’re reducing the time that used to be lost between stages,” Moskalchuk says.
Some waiting time is unavoidable in insurance repairs. Once a vehicle is disassembled, hidden damage may be discovered, the original estimate may change, and additional parts or approvals may be required. Moskalchuk is interested in a different interval: the period when the necessary decision has already been made, the part has arrived, or the previous operation has been completed, but the vehicle still does not move to the next stage.
The same logic can be traced through Moskalchuk’s research. In a 2021 publication on the digital transformation of automotive service, he examined the fragmentation of information systems, with customer management, repairs, inventory, and financial accounting operating in separate digital environments. In 2023, he continued exploring the issue at the software architecture level, connecting customer data, production operations, resources, finance, and management analytics through a unified information core.
Over time, the focus expanded from data integration toward the use of integrated data for analysis and decision support. In his 2024 study of artificial intelligence in the U.S. automotive service sector, Moskalchuk conceptualized this development as a progression from Automation to Predictive Analytics and Intelligent Management. His 2025 study applies this logic to the SynqRail platform, presenting it as an integrated environment that consolidates operational, financial, communication, and production data and creates a foundation for AI-based analytics, process automation, decision support, and business scaling.
Practical testing of the approach began at U.S. automotive businesses. In 2026, SynqRail was used by five independent companies across three segments: collision repair, car rental, and used-car sales. It was there that Moskalchuk’s idea about time lost between individual stages of work became most visible. The companies began responding to inquiries more quickly, missing fewer required actions, and keeping better track of jobs that required a next step.
The effect was particularly noticeable in collision repair, where a single missed task can delay everything that follows. At Zip Auto, the share of vehicles delivered later than the date promised to customers fell from 18% to 13%. Previously, about four out of roughly 15 scheduled callbacks could be forgotten or overdue; after SynqRail was implemented, that number fell to one or two. At the same time, the typical repair cycle decreased from four to six days to three to four days, while the number of jobs processed increased from roughly 1.5 per day to three or four.
Trumi Collision Center reported a similar result. The number of delayed repairs fell from about eight to six per month, a 25% reduction, while the typical repair time decreased from roughly five days to four. The change in customer follow-up was even more pronounced: missed calls, which previously occurred once or twice for every 10 scheduled contacts, became isolated cases after the system was introduced.
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Another result was equally important to Moskalchuk: a principle developed for collision repair proved applicable in businesses where vehicles move through entirely different operating cycles. At Nizo Luxury Rental, the average initial response time to customers fell from about 45 minutes to 25–30 minutes, while the share of customers who did not receive timely follow-up dropped from one in four to one in nine. At Rydex Auto Group, the initial response time fell from about 30 minutes to 15. At auto dealer Romcar, it decreased from roughly one hour to 20–30 minutes. Before the system was introduced, about half of prospective buyers received no second contact; with SynqRail, follow-up became a systematic part of the process.
Taken together, the individual figures point to a broader change. SynqRail does not repair a vehicle in place of a technician, nor does it eliminate objective causes of delay, such as waiting for a part, an insurer’s decision, or the completion of a technical operation. The platform addresses the time lost between those events: when someone needs to contact a customer, assign the next task to the responsible employee, check the status of a job, or identify an expected action that was never completed.
As insurance repairs in the United States become more complex, the definition of efficiency in auto repair is changing as well. Accurately assessing damage and completing the technical work are no longer enough; outcomes increasingly depend on how smoothly a vehicle moves through the entire process, from initial estimate to delivery back to the customer. At this level, SynqRail uses artificial intelligence to track the sequence of actions and identify delays between them in a timely manner. Early results indicate that this approach can reduce vehicle downtime, move workflows toward completion faster, and help repair businesses make fuller use of their operating capacity.
