Case 03 — 2025
Request Intake
Logistics automation
Requests arrived as emails, spreadsheets and scanned waybills. Eight operators retyped them into the accounting system. A pipeline does that now, and people only handle what is genuinely unclear.
- Client
- Logistics operator, 1,200 requests a day
- Industry
- Logistics
- Timeline
- 5 weeks, rolled out route by route
- Team
- 2 engineers, a dispatcher as domain expert
Outcome
- 1,200
- requests a day with no manual entry
- 8 → 2
- operators handling intake
- 11 min → 40 s
- from email to request in the system
The task
Every morning started with three hundred emails. An operator opened the attachment, found the addresses, weight and dates, and typed them into the system. One wrong address cost a run.
- 1,200 requests a day and 8 people on data entry alone
- Dozens of formats: emails, Excel, PDF, photos of waybills
- Typing errors only surfaced once the truck was on the road
- Half the volume lands inside a two-hour morning peak
What we built
We did not replace the accounting system. The agent sits in front of it: it reads the incoming message, extracts the fields, validates them and creates the request over the API.
- Parsing of the dispatch mailbox and attachments in any format
- Extraction of 18 request fields, each with a confidence score
- Address validation against a reference book and rates against the price list
- Unclear requests go to an operator's queue, not into the system
- An automatic reply to the sender with the request number
How it works
- 01
Incoming email
The dispatch mailbox is read automatically; attachments are unpacked and recognised.
- 02
Field extraction
Addresses, cargo, weight, dates and contacts are pulled into one structure.
- 03
Validation
Addresses are checked against the reference book, rates against the price list, duplicates are dropped.
- 04
Request created
The request goes into the accounting system over the API; edge cases go to an operator to confirm.
Stack
- OpenAI
- n8n
- FastAPI
- Postgres
- OCR
- TMS API
“They understood our process first and only then touched the models. That is why it actually works.”
What's next
Next: an automatic reply with timing and price right in the email thread, before the request even enters the queue.
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