A flat rule protects the wrong shipment. The real risk is somewhere else.

Cargo Intelligence is the trip score: the quantification of each shipment’s risk before it happens. It combines the variables the transport industry always knew were decisive but never computed together — the route (incident history per stretch, critical points, risk windows), the cargo (value, illegal-market liquidity — food, fuel, medicine and electronics lead the targets —, fractioning and attractiveness), the time (the urban stretch at dawn does not carry the same risk as the highway in the afternoon), the driver (the trip’s Driver Score) and the live context (seasonality, events and recent network intelligence). The result is an explainable per-shipment number instead of a hunch or a flat rule.

The problem it solves is structural. Brazil records around 8,570 cargo robberies a year, with losses between R$ 900 million and R$ 1 billion and 86.8% of incidents concentrated in the Southeast — and organized crime chooses stretches, times and cargo with growing intelligence. The defense, however, still answers with the policy’s flat rule by value: the same protection for trips of completely different risk. The effect is twofold: escort and decoy are paid where there is no risk, and the very shipment the criminals are watching is left exposed. A rule that pretends risk is uniform loses on both sides.

Calculating the score turns that pipeline into four practical uses. First, the dynamic RMS rule: escort, decoy, convoy and restricted window sized per trip, proportional to real risk. Second, planning: route and time chosen by risk, not only by distance, keeping the critical stretch and the dangerous window off the path. Third, pricing: freight and insurance with real risk in the price instead of the portfolio average. Fourth, underwriting: the insurer assessing the book shipment by shipment, enabling insurance products the flat-rule policy simply does not allow. Incident intelligence, which today lives in silos and reports, now calibrates the decision before the shipment leaves.

The differentiator is integration. Incident intelligence exists — the national logistics association has consolidated the country’s data since 1998, risk managers keep their own bases, insurers hold their portfolio loss history — but it lives in silos, and the shipment decision still follows the flat rule. The integrated trip score — geo-referenced incidents, cargo, window, driver and context in a single number — did not exist as a product. Kavuka brings together what each isolated player lacks: the scoring engine, the Driver Score as a trip variable and the ability to consolidate the dispersed intelligence, handled responsibly and under data-protection law from the first source, with a documented rule and an explainable score. Every trip carries a risk; now it has a number — before the shipment leaves.