AI automation for logistics paperwork and approvals

• Documents and forms. Details are pulled from BOLs (bills of lading), delivery receipts, invoices and PDFs, checked, and saved in the system they belong to. The same reading and checking drives routing guide checks before shipping.
• Billing capture. Work done on the floor, such as extra handling, relabeling or special storage, is recorded when it happens and matched to the client’s rate sheet, so it reaches the invoice instead of living in someone’s notes. Capturing billable warehouse work.
• POD checks. When a POD (proof of delivery) comes back, it is checked for a signature, a date and a match to the load before the invoice goes out. A missing or unclear one goes to a person. POD checks before invoicing.
• Requests and approvals. Each request is checked for missing details, sent to its approver and recorded.
• Inquiry routing. Inquiries from your website, email and forms are captured and assigned to the right person.
• Reports. The weekly report is assembled from your systems, so nobody copies numbers by hand.
• Smart apps. When a tool alone is not enough, we build a small app around the workflow. AI goes only where it helps.

AI is good at reading a messy invoice or a photographed BOL, but it is not always right. So we design each automation with checks around the AI step: required fields must be present, totals must add up, and anything that fails a check or looks unusual goes to your team for review. We plan it so nothing important is saved on the AI’s word alone.

We built MicroFlow, a self-hosted workflow platform on the open-source Activepieces project. For heavier jobs we write custom code in Python or Node with a PostgreSQL database. If your team already uses Zapier, n8n or Make, we can build there instead.

Where an AI model has to run on your own infrastructure rather than a hosted API, we choose the model, GPU and settings, test it on your own data, build the setup in your account and keep it running.

We start with one job your team repeats often and can describe step by step. We map who does it, which tools it touches and where it goes wrong. The first version handles the common cases and sends the unusual ones to a person. We add more once that version runs reliably.

1. Scope and quote. We map the job, its exceptions and the tools involved, and give you a fixed quote.
2. Run samples with regular demos. You watch sample documents and requests move through each step.
3. Hand over. You receive the source code and the repository. The full detail is on how we work.

Examples by industry: warehousing and 3PL and trucking.