Daniel Yun, Co-CEO of Willog
From warehouse floor to boardroom
Daniel Yun’s journey into supply chain technology began in a logistics warehouse, where he witnessed firsthand the inefficiencies and trust issues within cargo transportation.
One recurring problem was the inability to determine the causes of damage to temperature-sensitive cargo during transit. Willog built IoT sensor devices to capture trustworthy data and implemented AI analytics to flag anomalies before they occur.
Making invisible cargo visible
Enterprise systems such as ERP, WMS, and TMS track what is being shipped, how much, and when, but they miss the actual physical condition of cargo. Willog’s approach involves four stages:
- IoT devices, branded Willog Safe, capture physical data at the point of sensing.
- The data is combined with external context, such as weather and route information, to anticipate problems.
- The system prescribes what action should be taken.
- Finally, the entire sequence is preserved as verifiable evidence.
This approach feeds physical-world data back into the enterprise systems, turning vague suspicions into concrete, location-specific data.
The zero churn structure
Willog reports zero percent churn and 100 percent contract renewal across 2024 and 2025, figures that stand out even against strong SaaS benchmarks. Yun attributes this to how deeply the system is embedded in a customer’s operations.
“If we were simply providing one more dashboard, a customer could switch away at any time,” he says. “But Willog is embedded in the customer’s own processes — inbound, outbound, quality control, and regulatory compliance.”
Where the real moat lies
Real-time telemetry is becoming increasingly commoditized, with multiple providers now able to supply sensor data. Yun places Willog’s differentiation elsewhere, in the accumulated context around that data and the products built on top of it.
Over five years and across six industries, Willog has built up domain-specific knowledge of how different cargo types respond to particular conditions and where losses tend to occur.
The value comes from interpretation: “The same temperature reading only becomes valuable when you can interpret what it means for a specific pharmaceutical, and what it translates to as an insurance premium.”
Growing through references, not persuasion
Willog’s new contracts grew several-fold last year while customer acquisition cost fell, a shift Yun credits to reference-based expansion rather than any change in sales tactics.
Early on, without a track record, approaching large enterprises and government agencies was difficult. The company instead built credibility steadily with small and mid-sized customers.
Trust in sectors that cannot afford mistakes
Willog’s deployments include biopharma cold chains and overseas military logistics, sectors where a single failure carries serious consequences.
Yun says conservative buyers are less interested in how advanced a system is than in whether failures can be explained afterward. Willog’s AI judgments are kept traceable, with the underlying data preserved as evidence rather than treated as a black box.
From monitoring to insurability
Yun says the realization that shipment data could underpin insurance came from recognizing that proof of what actually happened in transit could be used to price risk by measurement rather than estimation.
What comes next
Willog’s roadmap includes further expansion into Europe and Southeast Asia, alongside a longer-term ambition to go public. The realization that shipment data could underpin insurance came from recognizing that proof of what actually happened in transit could be used to price risk by measurement rather than estimation. In this model, AI prediction and prevention reduce the probability of incidents occurring at all, while insurance, priced on measured data, covers whatever residual risk remains. “If prediction and prevention are the domain of reducing risk, insurance is the domain of taking responsibility for the risk that still remains,” he says.
Sequencing mattered too. Rather than asking customers to trust an unproven AI system outright, Willog first cleared some of the strictest verification standards available — international transport for Corning, global knock-down transport quality management with Hyundai Glovis, and cold-chain transport for the ROK Army General Supply Depot. Passing military supply logistics vetting, in particular, gave the company more credibility with subsequent conservative clients than any pitch could.
On Southeast Asia specifically, Yun pushes back on the idea that Willog is simply a sensor vendor.
Looking further ahead, Yun describes the company’s ambition in structural terms: an infrastructure answering what physically happened, what is likely to happen next, and what that risk is worth, with data, AI, and insurance interlocking on a single foundation.
