Operational AI gives you insight into vehicle location, driver status, and loads in real time. Traffic and weather conditions can be predicted and routes modified to avoid high traffic, bad weather, and even routes that are not efficient. Unexpected issues like steep grades, detours, or accidents can impact fuel efficiency, let alone delivery status. Routing around weather incidents like storms, icy roads, or other hazards can save time and reduce maintenance requirements. Operational AI in logistics can be a powerful edge in fleet visibility. And it can be deployed incrementally, over time, for improved learning and usage, and to amortize costs.

Many logistics firms target multiple market segments. For example, the portable storage industry serves two distinct markets. The B2C market is the most immediately recognizable. We’ve all seen containers on our residential streets: popular among college students, military families who must move often, or with downsizing retirees. B2B customers, typically construction companies, large retailers, or municipalities, need to store equipment, tools, supplies, excess retail inventory, or office furniture during construction projects or, in the case of retailers, during peak shopping periods. Operational AI can address routing, maintenance, and availability issues for both markets using the same systems, even though each market imposes different demands.

Detect delays, disruptions, and performance risks early — enabling proactive intervention before service levels are impacted rather than reactive response after the fact.

Patterns derived from historical data can be used to build a model of your logistics business. Once you have a baseline of your delivery data, the AI can begin finding ways to improve routing, fuel efficiency, delivery time-of-day, driver efficiency, and more. Route analysis and maintenance review can trigger driver alerts that help drivers find better routes, more efficient driving techniques, and safer roads through dangerous locations. These improvements can lead to improved SLA outcomes, potentially leading to higher confidence and justifying higher rates. Operational AI can use historical paper logs to find patterns in delivery: routing, efficiency, fuel costs, and recurring customers.

Asset and cargo intelligence can provide improved margins due to improved delivery routing, faster loading and unloading, better fuel consumption, decreased damage and lowered insurance claims. Operational AI systems can identify cargo in multiple ways: weight, dimensions, volatility, destination, and more. Operational AI paired with sensor technology can track delivery times, elapsed delivery time, and delivery reliability. You can define quality scales that allow the AI to learn which routes are best for which types of items, which types of items should be shipped separately from one another, which loading configuration is most efficient, which weight distribution is most fuel efficient and safe.

Bridgera Operational AI solutions are not generic off-the-shelf solutions. We tailor our solutions to your specific requirements and workflows. Don’t expect a tear-down and build-from-scratch type of engagement. We work with the systems you have and help you squeeze out as much value as possible. Your existing ERP, MES, CRM, and IoT systems continue to provide quality state data about your operation. You do not need to go through major data cleansing and reorganization projects before putting Operational AI solutions to work. Often, our systems will find the most efficient and effective use of your data, just as it is.