How a unified AI platform can boost turnaround times for shipping companies

Insights

• High‑volume global shipping was constrained by manual, fragmented, and exception‑heavy workflows.
• Low automation was driving errors, delays, compliance risk, and revenue leakage.
• An AI‑first platform unified workflows, rules, and tribal knowledge at global scale.
• Intelligent automation lifted straight‑through processing and cut turnaround times dramatically.
• Automation scaled from 10% to 70%, delivering speed, accuracy, and operational resilience.

In logistics and shipping, every shipment counts and every second compounds. High volumes and tight margins make operational speed, accuracy, and cost control critical to staying profitable.

As global supply chains become more complex and customer expectations are shaped by players like Amazon, DHL, FedEx, and Maersk, real-time visibility and rapid fulfillment are now baseline requirements. Manual processes in areas such as documentation, customs clearance, routing, and invoice reconciliation slow operations and increase the risk of costly errors.

Using artificial intelligence (AI) and automation streamlines processes, reduces delays, improves turnaround time (TAT), and allows personalization for customers. In an industry where disruptions ranging from geopolitical tensions to port congestion and shifting government policies related to import and export are constant, intelligent workflow automation provides the agility and resilience companies need to stay competitive. That said, it also requires organizations to reimagine their business operations to get the most value from AI, instead of treating AI and automation as add-on capabilities.

The business challenge: Operational bottlenecks

A global shipping and logistics company, one of the world’s largest container shipping lines, which operates in over 150 countries and offers maritime transport, port operations, and end-to-end logistics solutions, was facing multiple operational challenges. The company employs thousands of full-time employees across its global business service centers in APAC and Europe.

These teams support over 80 processes that involve long, complex, and manually intensive workflows, heavy documentation, and domain expertise — particularly related to bill of lading (BOL), bookings, and freight audit and invoicing (FAI). The activities span functions such as operations and logistics, with wide variation in shipping policies and preferences across those regions and customers.

Some of the challenges that the client faced:

• Highly manual booking and documentation workflows: The company was using a complex container booking system with a multichannel real-time booking process. Large volumes of BOL requests flowed in from customers across 116 countries globally, over multiple channels including via electronic data interchange (EDI), web, email, and phone calls. Much of the information in these channels, related to shipment details, charges, and terms, was unstructured. With only 10% of the processes automated, employees had to manually read and understand multiple documents and policies, extract and reenter data into multiple systems, and crosscheck information before or while processing the requests. Additionally, it was a challenge to find the right talent with expertise in this domain and train those without adequate experience. The organization was also looking to automate the invoicing that was being handled in four countries.
• Low automation levels affecting business operations and the bottom line: Inaccuracies from manual filing by the employees were leading to customs filing errors, high booking cancelations, disputes with customers, fines, and reputational risks, not to mention poor customer experience when customers were inadvertently overcharged. There were also instances of the reverse, where underbilling was leading to revenue loss.
  
• Complex, exception-heavy FAI processes: The existing FAI process required multiple checks — shipment eligibility, freight rates, event dates, business rules, and customer-specific exceptions — often triggering manual reviews across teams. The client aimed to simplify the rate-filing system to handle these combinations quickly and smoothly.
• Difficulty managing regional variations: Teams struggled to keep track of regional variations when handling shipments between ports across regions. The employees handling the requests were needed to understand the customer’s booking request, apply relevant regional rules and policies, factor in regional nuances such as product classification, tariff codes, BOL structure, whether documents must be original, digital, notarized, or stamped, and customs declarations, and ensure the shipment reaches on time and within the specified requirements. The client also had to account for their customers’ specifications related to shipping: the number of batches that containers need to be divided into, and specific locations for billing, or landing.
  
  

  With high volumes of shipping requests being processed through largely manual workflows, the process was prone to human errors and risks. The fines emerging from service level agreement (SLA) breaches, and lapses in adhering to regional shipping policies, and legal and compliance requirements, were leading to higher operational costs.

To enable transformation across these business services, the client needed an enterprise-governed, unified platform capable of intelligently automating workflows, integrating disparate systems, minimizing risk and human error, and improving accuracy and operational efficiency.

The implementation process

EdgeVerve partnered with the shipping company to help it with its global business services (GBS) transformation by implementing the AI Next  platform. This initiative transformed multiple business functions from customer service request processing to core operations.

It was an AI-first transformation – which means redesigning the business, its processes, and decision-making with AI as the starting and pivotal point rather than as an add-on – of about 16 initiatives, including those involving BOL and FAI. This unified GBS solution enabled 4,000 GBS domain specialists globally to help them work more efficiently.

• The implementation involved a platform led, AI first transformation that orchestrated over 90 interfaces across over 20 systems into a single, harmonized processing layer. A centralized decision framework digitized more than 8,000 tribal customer preference policies and embedded 116 country specific standard operating procedures, enabling consistent and compliant execution at global scale. AI capabilities were applied to interpret unstructured free text shipping instructions in 16 languages, allowing exceptions to be auto classified and routed intelligently. This transformation drove straight through processing (STP), across workflows spanning close to 4000 steps, while handling over a million transactions per month on a unified platform.

  A platform-led, AI-first transformation unified over 90 interfaces across over 20 systems into one harmonized processing layer.

  
• EdgeVerve created an automated flow that takes data from where it’s collected in the client’s system and delivers it to where it’s needed. For instance, in case of BOL generation workflow, there are separate pipelines on merging duplicate requests, splitting requests, fetching data, and extracting data including remarks to process a request. This means that required data can be brought in more quickly and with less manual effort to accomplish a workflow.
• AI-powered document processing enabled efficient extraction of booking and shipping instructions/remarks shared by a customer, such as the window for delivery, type of packaging used, and so on. It does this by going through the shipping request documents such as emails, and reading unstructured data like a human but faster, to process the request.
• Enabled exceptions and business rule management with rule engine capabilities to configure country-specific exceptions and business rules. The solution applies location-specific policies and rules to the request, which helps the client comply with local laws. This meant faster and better decisions in processing requests, with digitized documents, extracted data, end-to-end visibility, and insights.

Measurable outcomes: The impact of AI and automation

A platform such as EdgeVerve AI Next is deployed in an incremental manner — in small, manageable phases rather than all at once.  Agile methodologies are used to reduce tech debt through iterative updates, ensuring ongoing support and upgrades that meet industry changes and customer needs. This helps organizations achieve faster user adoption.

• Automation of processes: Fewer human agents were required to do those tasks, freeing up their time to take on more requests, and to focus on more business-critical tasks that required more human involvement. It helped tackle the challenge of finding skilled talent by being able to perform many of the manual tasks such as BOL draft generation, booking confirmation, freighting and so on with fewer errors, though it must be said it’s essential to keep humans in the loop to ensure AI delivers the best possible results. The initiative resulted in a rise in process automation from 10% in the baseline state to 70%.

  Fewer agents were needed, freeing them to handle more requests and focus on higher-value, human-critical tasks.

• Rise in STP: Straight through processing for cases that earlier required human involvement rose from 0% to 70% driven by platform-led digitization of tribal knowledge, unification of fragmented workflows, and implementation of automation and AI.
• Reduction in TAT: The workflow TAT showed measurable improvement through the use of AI-driven orchestration, with the platform coordinating and executing the entire workflow. For instance, freight auditing and invoicing TAT was reduced from 24 hours to just 30 minutes.

For shipping companies operating at global scale, a unified AI platform delivers a strategic control tower. By embedding intelligent automation into documentation, routing, customs processing, invoicing, and cargo tracking, organizations can significantly reduce manual errors and improve TAT. The result is improved agility, reliability, and a positive customer experience in an increasingly demanding global marketplace, while being able to scale.