FreightWise is stepping up its use of artificial intelligence in transportation management with the launch of Kuebix AI, a redesigned transportation management system (TMS) intended to address some of the most persistent challenges facing shippers: complex route planning, disconnected business systems, unreliable delivery schedules and time-consuming freight audits.

Announced on October 20, the platform brings FreightWise and Kuebix customers together under a single technology environment. It supports less-than-truckload (LTL), truckload and parcel transportation, with a particular focus on small and mid-market shippers.

The company is positioning the new solution around a practical application of AI, moving beyond basic cost optimization to help planners determine whether transportation plans can actually be executed under real-world operating conditions.

Speaking with FreightWaves at the F3: Future of Freight Festival in Chattanooga, FreightWise CEO Chris Cochran explained that the company's strategy is built entirely around the shipper community, rather than freight brokers.

Combining FreightWise and Kuebix into a single platform

The launch of Kuebix AI is also the culmination of a major phase in FreightWise’s technology consolidation strategy.

Following Kuebix’s acquisition in 2023, the company operated two separate systems: FreightWise TMS and Kuebix TMS. The new platform combines the two customer bases into one technology stack, one team and one product roadmap.

“This structure will allow product enhancements and new features to reach customers faster,” said FreightWise.

The development process involved porting the existing capabilities of Kuebix into FreightWise’s existing native application that was originally developed for its managed transportation operations. The aim was to retain the functionality longtime Kuebix users were accustomed to, while upgrading the underlying infrastructure and integrating AI into key workflows.

The team spent the past year rebuilding the platform while retaining the capabilities that Kuebix customers had come to rely on for nearly two decades, Cochran said.

Thousands of users are already using Kuebix AI. FreightWise also expects to see more customers migrate to its standalone SaaS offering over the next year.

Making complex multi-stop truckload planning clearer

One of the platform’s core innovations is multi-stop truckload routing, an area where traditional TMS solutions can struggle to reflect the real-world constraints of freight operations.

Traditional systems may calculate the most optimal route but not take into account delivery appointment windows, driver availability, facility schedules or waiting times. The planners are then left to manually identify problems, often without knowing why the system selected a particular route, or other scenarios are at hand.

Kuebix AI wants to move away from this narrow approach to a more flexible planning environment.

The platform shows on a single screen several possible routing scenarios, and the benefits and limitations of each are highlighted. One route may involve extra mileage to meet a delivery appointment, while another may save transportation costs but require the customer to accept a new delivery time.

Planners can choose the option that best fits operational priorities and take actions directly in the system. This may include managing customer expectations or searching for retailer shipments that might involve extra fees or costs from damage.

The idea is to eliminate the need for transportation teams to exit their TMS when a proposed route is not viable.

This is supported by two AI-powered capabilities. AI-enabled service time calculations in delivery planning consider hours-of-service regulations, wait times, loading/unloading requirements and facility hours of operation. Multi-stop AI routing then calculates how possible different stop sequences are and suggests an appropriate route.

The approach is designed to make delivery commitments more realistic and reliable, FreightWise says.

Simplify system integration and reduce the need for ongoing IT intervention

FreightWise will take a look at another major operations challenge beyond transportation planning — integrating the multiple systems used to manage shipments.

Many small and midsize businesses have small IT departments with limited resources. The systems feeding order information to a TMS may be built on older technology that does not support modern integration methods.

To tackle this challenge, FreightWise built Kuebix Connect, a no-code middleware that gives business users more control over system connections.

Via a visual interface, users can map fields and create relationships between their TMS and other enterprise applications such as warehouse management systems (WMS) and enterprise resource planning (ERP) platforms.

There is also artificial intelligence in the integration layer, to check incoming data feeds for possible errors.

“Data problems, like a bad character, don’t take much to stop orders from entering the system and having freight sit in a warehouse,” Cochran said. Kuebix Connect is built to detect these failures, fix some issues and help users find what is causing them.

IT teams are still responsible for issuing credentials and security checks. But the approach is to decrease the need for their direct intervention when an integration hits a routine snag.

AI-powered dashboards that explain transportation performance

A third component, Kuebix Intelligence, focuses on improving visibility into transportation expenditure and operational performance.

The company describes the solution as a collection of AI-backed dashboards covering freight spending by location, carrier and transportation mode. Rather than simply displaying performance indicators, the system is designed to explain the factors behind changes and deviations.

Cochran highlighted the advantage of having rating, routing, freight audit and payment functions within the same platform. Because settlement information is integrated rather than held by an external audit provider, FreightWise believes its AI can draw on a more comprehensive dataset.

This allows the system to investigate why a key performance indicator (KPI) is underperforming and identify where the problem originated, without requiring financial executives to wait for a logistics analyst to provide an explanation.

The platform also introduces AI-powered freight audit exception resolution. This capability compares quoted transportation rates with final invoiced amounts, identifies discrepancies, calculates their financial impact and recommends strategies for disputing charges with carriers.

An intentional focus on real-world AI applications

FreightWise says it was slow to get to the AI market. Cochran estimated the company was about six to eight months behind the original schedule.

The delay, he said, was a conscious decision made out of concern about the trend of embedding AI into software products without a clear operational purpose.

He thinks some of the early versions used chatbots that had incomplete information and not enough context. Although users may have used these tools, they did not necessarily deliver lasting improvements or address major business challenges.

So FreightWise chose to wait until it could embed AI into working processes.

The company calls this philosophy operationally executable AI: technology designed to solve real-world problems, not just a feature of a product that employs artificial intelligence.

Chris Haarmeyer, CTO of FreightWise, echoed this point, noting that development began with issues raised by customers and internal teams, including delivery schedules that don’t take into account driver hours-of-service limits and appointment windows.

Data protection was also on the agenda at the launch. “We make all of our AI features opt-in,” Haarmeyer said. “We keep customer information secure and we never use it to train third-party models.”

Data quality and human relationships still matter

Cochran said he’s confident in the potential of AI, but that its success depends heavily on the quality of the information it gets.

Low-quality data can cause artificial intelligence systems to make wrong conclusions or hallucinations. And, as such, he believes that companies need trustworthy, centralized information sources to realize the full capabilities of AI-driven logistics applications.

Thus, businesses that lack a clean, consistent source of record will be at a disadvantage compared to competitors who have built stronger data foundations.

Cochran also made a clear distinction between automating operational tasks and managing customer relationships.

He doesn’t see AI replacing direct human contact in customer support or account management. He thinks customers should be able to talk to a real person when they have urgent difficulties, rather than a chatbot.

He argued that AI is not a universal fix. Commercial teams still have to get orders. Trucks have to be loaded. Goods have to reach their destinations. However, shippers who fail to implement relevant AI capabilities risk losing control of their cost to serve as operational complexity increases.

What’s next for Kuebix.ai?

Starting in 2027, FreightWise will launch additional AI-driven capabilities and continue the migration of existing Kuebix customers to the new platform.

The company’s priorities are still focused on meeting the practical needs of the business, making it easy to integrate with the shipper’s existing technologies, using AI to find and fix data errors, and improving the quality of information for operational decision making.

For shippers, the real test will be whether these capabilities translate into more reliable delivery commitments, fewer integration disruptions, better visibility into freight costs and more effective transportation management.

FreightWise is leveraging Kuebix AI to create a model where artificial intelligence is not just a decision recommender, but an operational tool integrated directly into the processes that move freight.