Tive and the Business of Making In Transit Loss Measurable

Tive exists because most logistics losses are not sudden failures. They are gradual deviations that go unnoticed until value is already destroyed. Temperature drift, dwell accumulation, route deviation, and handling shock typically occur hours or days before a shipment is declared spoiled, delayed, or rejected. Traditional logistics systems detect these failures after delivery. Tive was built to move detection into transit, when intervention is still possible.

According to the World Economic Forum, supply chain disruptions cost companies an average of 45% of one year’s profits every decade. A meaningful share of that loss comes from in-transit failures rather than planning errors. In cold chain logistics alone, pharmaceutical industry estimates frequently cited by regulators and trade publications place annual losses from temperature excursions at roughly $35 billion globally. These losses are not driven by widespread failure rates. They are driven by the catastrophic cost of rare failures.

Tive’s core product is not visibility software in the traditional sense. It is a shipment-level sensing system built around cellular IoT hardware paired with real-time analytics. Each tracker travels with the freight and independently captures location, temperature, humidity, shock, light exposure, and dwell time across road, ocean, air, and rail. This design matters because most visibility platforms rely on carrier milestone updates or vehicle-based GPS, which fail during transloads, port dwell, or handoffs across modes.

The technical specifications are designed for long-haul and cross-border moves. According to Tive product documentation and customer materials, its trackers support temperature accuracy within half a degree Celsius, operate across a wide temperature range suitable for pharmaceuticals and food, and maintain battery life long enough to cover multi-week ocean journeys. Measurement frequency can be set at minutes rather than hours, allowing deviation trends to be detected early rather than logged after the fact.

The economic value shows up most clearly in high-value and regulated supply chains. Pharmaceutical Commerce and FDA-cited industry reporting consistently note that a single temperature excursion can invalidate an entire shipment, triggering destruction, retesting, or regulatory holds. Retesting alone can delay product release by weeks and cost tens or hundreds of thousands of dollars per SKU. Tive customer case materials describe shipments valued in the seven-figure range where early detection allowed corrective action, avoiding both write-offs and downstream launch delays.

Food and beverage supply chains show similar economics at different scales. According to the Food and Agriculture Organization, global food waste exceeds $400 billion annually, with a meaningful portion tied to handling and transit failures. In perishable lanes, avoiding one rejected load can offset months of monitoring cost. The value proposition is not reduced freight spend. It is avoided loss, avoided chargebacks, and avoided reshipment.

Delay intelligence is another lever. McKinsey estimates that supply chain disruptions can cost companies 30% to 50% of one year’s EBITDA over a decade. In automotive, electronics, and industrial manufacturing, late inbound components can shut down production lines where downtime costs reach tens of thousands of dollars per hour. By detecting abnormal dwell or route behavior early, Tive allows teams to reroute, expedite, or reallocate inventory before the disruption propagates.

The company’s scale supports this positioning. Tive has publicly stated that it has shipped more than two million tracking devices into active use, which is a meaningful threshold in a hardware-backed category where many deployments stall at pilot scale. Its customer base spans enterprise shippers, manufacturers, and logistics providers operating global networks rather than purely domestic lanes.

Capital raised aligns with that ambition. In 2024, Tive completed a Series C financing that brought total funding above $70 million, backed by growth-stage investors focused on industrial and supply chain technology. That capital has been deployed toward global cellular coverage, battery life improvements, sensor reliability, and analytics depth rather than rapid, low-discipline expansion.

Insurance dynamics further reinforce the model. According to Marsh and other global insurance brokers, cargo insurance premiums have risen sharply in recent years, particularly for temperature-sensitive and theft-prone lanes. Underwriters increasingly require evidence of active monitoring and intervention capability. Tive’s data provides auditable proof that shipments were monitored continuously and that corrective action was attempted when deviations occurred, influencing both underwriting decisions and claims outcomes.

Where Tive is strongest is in freight where the cost of failure materially exceeds the cost of monitoring. Where it is weaker is in low-value, low-risk domestic freight where margins cannot support hardware instrumentation. That constraint is structural, not tactical. Tive is not built to be universal. It is built to be decisive in the lanes where failure is unacceptable.

At a deeper level, Tive reflects a shift in how supply chains manage risk. Planning systems assume execution will follow intent. Shipment-level sensing acknowledges that execution often diverges and that value depends on how quickly that divergence is detected. By turning in-transit risk into measurable, time-bound signals, Tive reframes logistics from post-mortem explanation to real-time control.

That is the business it is actually in.