More and more, artificial intelligence is ingrained in our everyday lives. From facial recognition on our smartphones to fraud-detection systems used by banks; these systems rely on data to perform tasks faster and more efficiently than humans. So when it comes to time-critical logistics, you would think that AI is commonplace, right? Time-critical logistics needs to move shipments faster, more accurately, and efficiently than any other type of logistics. Artificial intelligence is a proven technology that accomplishes this feat. Yet, most logistics companies have not applied these modern tools to daily operations. They are still confined by the technological limitations of yesteryear.
Propelling Time-Critical Logistics into the 21st Century
Airspace is one of the only time-critical logistics companies to effectively utilize artificial intelligence and machine learning in everyday operations. This has landed the company on the 2022 CNBC Disruptor 50 List and has caught the attention of notable leaders within the tech and logistics industries.
Airspace aims to bridge the gap between the outdated, traditional processes of logistics and today’s need for faster, more accurate shipping. Patented technology analyzes years of historical data that includes: flight patterns, weather conditions, and other impactful factors needed for fast time-critical shipping. With the help of machine learning, this tech can make accurate predictions on travel duration from pickup to delivery for small parcel, next-flight-out, and freight shipments.
To keep up with the ever-changing needs of the world around us, Airspace consistently revisits its existing technology to scale and improve it. Airspace is in the business of making time-critical logistics processes more efficient, accurate, eco-friendly, and of course, cost-efficient for clients. Airspace has mastered small-parcel shipping which typically includes organs for transplant or compact mechanical parts–virtually anything that can fit in a sedan or compact SUV. The latest application for this advanced tech is for larger, freight-sized shipments such as airplane and factory parts. But the reality is, this patented technology has endless applications. As Airspace continuously builds and develops AI/ML technology, its finding new ways to streamline the time-critical shipping process.
Solving Old Problems with New Tech
Some of the biggest issues in time-critical logistics include rising costs, labor and shipping shortages; and managing complex systems. Airspace is taking a modern approach to these centuries-old issues.
By utilizing historical data, machine learning, and artificial intelligence, Airspace is building a self-sufficient system. Starting with the Airspace Customer Portal. This convenient order-placing system allows current Airspace customers to input their shipment dimensions, pick-up and delivery locations, and other pertinent information. The algorithmic system draws upon its bank of historical data to instantly return a quote with the best rates and routes. Then, allows the customer to find their preferred airline, departure time, arrival time, and more, by allowing them to filter by these fields. Not only does the platform provide a stress-free way to place orders at the customer’s convenience, but it helps all parties save on cost, time, and manpower.
The same method of utilizing historical data and algorithmic solutions has been applied to the creation of the Airspace employee scheduling system. This system considers the times of day when most orders are placed and when the highest volume of customers is active. This allows Airspace to schedule the optimal number of employees to assist with active orders and therefore, provide the best customer experience.
This application of AI and machine learning help with other parts of this complex process, too. Anything from identifying incentives for contracted drivers to what kind of mobile apps would be helpful to customers, progress with the help of AI. With every update to the patented technology, Airspace chips away at the large issues apparent in time-critical logistics.
Better Tech, Better Customer Experience
In addition to the issues regarding process and procedures, Airspace has a goal to improve overall customer satisfaction. With any courier, customers must be able to trust that their most important shipments are in good hands. They demand need speed, efficiency, and above all, reliability. This is why Airspace lets computers do tasks that would typically take hours. It finds the best shipping rates faster. It sorts by preferences faster. It generates the best routes faster.
Airspace consistently builds on its logistics technology with features that provide a better customer experience. By constantly re-designing, testing, and developing the current system, developers can ensure that their technology continues to do the job that’s intended.
The team headed by Ksenia Palke, the Director of AI at Airspace, has become a well-oiled machine. Palke says, “We run several experiments simultaneously to see what’s working for our customers and team. We’ve really nailed this experimenting process so we can roll out new features and updates within weeks rather than months.” This quick turnaround time has created ebb-and-flow flexibility that cannot be found with any other time-critical logistics company. It enables the Airspace team to listen to customer needs, enact an action plan, and quickly identify other aspects that could benefit customers.
The impact of utilizing AI and ML for time-critical applications is significant. It eliminates unnecessary steps in an otherwise very segmented process. For time-critical logistics, this frees up so much time and energy that should be spent moving shipments. A full explanation of how these processes have been streamlined was captured as part of CBS News Innovation and Disruption Leaders series.
Could the world ever go back to shipping without AI?
Sure, but why would we want to? We have to understand that in any process where humans are involved, there is a chance for error. The more people involved, the higher the chances. Due to the severity of time-critical shipping, people expect to have virtually no errors.
Artificial intelligence and machine learning help to eliminate as much human error as possible. With any time-critical shipment, there are so many people, facilities, and external factors involved. Palke said it best, “Time-critical logistics is inherently stressful. Whether you’re awaiting an organ for transplant or a crucial mechanical part, you’re battling against so many uncontrollable factors. Our job at Airspace is to fully understand the controllable factors. If you can predict what is in our control, we can prepare for what is not.” Palke continues to say, “Ultimately, we want to do everything possible to alleviate the stress our customers face daily. We’re constantly designing and developing systems that take the stress out of time-critical logistics. If you think about it, a lot of the stress stems from human error. With AI, we eliminate a lot of human error and therefore, a lot of stress.”
Airspace is filling a major void within the time-critical logistics industry. Those efforts, rooted in technology, have helped hundreds of thousands of lives.
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