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same carrier network, document structures and data quality can vary widely.
Historically, freight audit, payment and transport management platforms relied on rigid rules and templates that struggled to adapt. As operations expanded globally, organizations were forced into extensive manual intervention, increasing cost, risk and processing time.
AI-based systems address this by interpreting documents according to structure, intent and business relevance. Innovators such as nVision Global, PayCargo and WOWL use this approach to manage variation dynamically.
“ This allows new transportation providers, regions, formats and exceptions to be handled dynamically, without lengthy reconfiguration cycles or operational disruption,” Griswold said.
AI-enabled platforms interpret freight documents based on“ context, structure and business intent,” allowing them to understand new formats, transportation providers, languages and regulatory
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“ This makes it possible to onboard new regions and partners at a speed that was previously unrealistic,” Griswold added.
Freight audit, transportation management and claims processes long shared the same limitation: systems could process only what they were explicitly told to recognize. If a document did not match a predefined format, the process broke down and human intervention became necessary.
“ Scale came at the expense of accuracy, and global expansion increased operational risk rather than insight,” Griswold said.“ AI has fundamentally changed that equation.”
AI is used by nVision to move beyond rigid automation into adaptive intelligence, enabling systems to flex to real-world transportation complexity rather than requiring clients to standardize operations around the software, he explained.
This industry shift is particularly visible in accounts payable workflows.
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