Freight keeps moving when the paperwork does.

Logistics document automation uses AI to extract, validate, and route the paperwork transportation and logistics operations depend on, including bills of lading, proofs of delivery, invoices, and customs documents, so shipments, billing, and compliance move forward without manual data entry or a growing exception queue.

super.AI extracts and validates the data on each bill of lading and proof of delivery, matching it against the shipment record and flagging mismatches before they cause a hold. Documents are processed without a fixed template, so variation between carriers and customers does not break the workflow.

No. super.AI layers onto your existing TMS, WMS, or ERP as a validation step ahead of it, rather than replacing it. There is no infrastructure overhaul and no new system for your team to learn; validated data simply flows into the systems you already run.

Accuracy depends on the implementation, but CHI Cargo achieved 95% accuracy on real-world datasets during its pilot with super.AI. After rollout, the company reduced manual review hours by 92% and went from reviewing 50% of documents to processing and validating 100%.

Implementation timelines vary by scope and document volume, but one customer, CHI Cargo, was live in three weeks. Because super.AI connects to your existing TMS, WMS, or ERP as a document layer rather than replacing it, most teams move from evaluation to a working proof of concept in weeks, not quarters.