Logistics companies cannot safely leverage proprietary shipping data to train AI models without risking trade secret theft and legal liability

Freight and logistics companies accumulating valuable operational data face a critical dilemma: they need to use this data to build competitive AI-powered software, but doing so exposes them to massive legal and financial risk if data is misappropriated or used without proper safeguards. Current solutions lack clear frameworks for secure data handling, IP protection, and evidence preservation, leaving companies vulnerable to costly litigation and unable to confidently monetize their data assets through AI development.