AI Automation for supply chain and logistics company

Project Overview

We are building an AI-powered automation solution for freight brokers, 3PLs, logistics companies, and transportation companies.

We are looking for an experienced AI/automation developer to help us design and build an initial MVP that automates repetitive logistics operations involving emails, shipping documents, and Transportation Management Systems (TMS).

This is NOT a project to build a new TMS from scratch. The goal is to build an AI automation layer that integrates with a company's existing systems.

Initial MVP – AI Load Entry Automation

The first workflow we want to build is an AI-powered Load Entry Agent.

Example workflow:

Customer sends a load tender / shipment request through email.
The system monitors a designated inbox and identifies relevant shipment emails.
AI extracts shipment information from the email and attached documents.

Information may include:

Customer
Origin
Destination
Pickup date/time
Delivery date/time
Equipment type
Weight
Pallet count
Commodity
Reference/PO numbers
Special instructions
The system validates required information.
If required information is missing or uncertain, the shipment should be flagged for human review rather than automatically processed.
Valid shipment information is sent to the TMS through an API where available.
The system records the transaction and provides an audit trail showing what information was extracted and what actions were taken.
A human operator should be able to review/approve exceptions.
Future Automations

This initial project may expand into additional logistics automation modules, including:

AI freight quote generation
Shipment tracking
Automated customer shipment updates
Delay/exception detection
BOL (Bill of Lading) processing
POD (Proof of Delivery) processing
Carrier invoice processing
Freight invoice auditing
Customer service automation
Carrier onboarding
Email operations automation
TMS/WMS/ERP integrations

We would prefer to work with someone who can continue developing these modules after a successful MVP.

Technical Experience We're Looking For

Experience with several of the following is preferred:

OpenAI APIs / LLM applications
AI agents and structured data extraction
Python and/or JavaScript/TypeScript
REST APIs and webhooks
n8n, Make, or similar workflow automation platforms
Microsoft 365/Outlook and/or Gmail integrations
PDF/document processing
OCR/document extraction
PostgreSQL or similar databases
Azure/AWS/GCP
TMS/WMS/ERP integrations
Authentication and API security
Docker

Experience specifically with logistics, freight brokerage, transportation, supply chain systems, or TMS integrations is a major plus.

Important Requirements

The system must be designed for reliability and production use.

We do NOT want an AI system blindly performing actions when it is uncertain.

The solution should include:

Confidence/validation rules
Human-in-the-loop approval
Error handling
Logging
Audit history
Secure credential management
API retry/failure handling
Ability to review AI-extracted information before submission

Architecture should also allow us to support multiple customers in the future.

What We Need From You

When applying, please answer the following:

Have you built AI workflow automation systems used in production?
Have you integrated with a TMS, WMS, ERP, CRM, or similar business platform? Which ones?
Have you built systems that automatically process incoming emails and attachments?
What would you use to extract structured shipment information from emails, PDFs, BOLs, PODs, and other documents?
How would you prevent incorrect AI-extracted information from automatically entering the TMS?
Would you recommend n8n/Make or a custom Python/TypeScript backend for this project, and why?
How would you architect the system so we can eventually support multiple logistics customers?
Please provide examples of similar AI automation or integration projects you have built.
Initial Deliverables

For Phase 1, we expect:

Solution architecture
Working email intake workflow
AI shipment data extraction
Attachment/document processing
Structured JSON output
Data validation
Human review/approval process
TMS API integration or test/mock integration
Logging/error handling
Basic administration interface or dashboard
Deployment documentation
Source code
Technical documentation
Relationship

We are interested in establishing a long-term relationship with the right developer or team.

The successful developer may continue working with us to develop additional logistics automation modules and deploy/customize the platform for future clients.

Please start your proposal with the words "LOGISTICS AI" so we know you have read the complete project description.