Automate Transport Request To Tms With Ai

Turn unstructured transport requests into executable TMS orders

Transport orders often arrive as emails, PDFs, or notes with pickup & delivery instructions. Interpreting them manually is slow, error-prone, and costly. Hyperfox uses AI to extract transport data, validate business and delivery rules, and create clean transport orders in your TMS.

Dispatch console with illuminated operator screens and keyboards in a transport control room.

Challenges in transport order processing

Logistics mission-control room with rows of operator stations facing large situational displays.

Managing transport request emails manually creates delays and inconsistencies, which impact planning, execution and customer satisfaction. Common challenges include:

  • Transport details buried in free-text emails and attachments
  • Errors in pickup/delivery locations, dates or references
  • Manual retyping into TMS causes mistakes and delays
  • Lack of visibility into transport intake workflows
  • No validation against operational constraints before execution

Key Hyperfox Capabilities For

AI-driven transport order automation

  • 1

    AI extraction of transport details

    Extract structured pickup, delivery, dates, references and special instructions from email text, PDFs and attachments, even when unstructured.

  • 2

    Automated delivery validation

    Check delivery windows, locations, route constraints and references against operational rules before creating transport orders.

  • 3

    Direct TMS integration

    Push validated transport orders directly into your TMS in the right format, eliminating manual entry and rework.

Powering operations for

T'SASManna FoodsPelican RougeCoeckPharmapuntJomaFormula BathroomsBergHOFFDuplastDistrilogPolySealGoboTheumaHamletRevoganVannesteHansaFlexSapim

The value of automating transport orders

  • Eliminate manual transport order entry and retyping
  • Reduce errors in pickup/delivery details and timings
  • Increase capacity without adding back-office resources
  • Improve TMS accuracy and planning efficiency