Why this matters
Logistics teams are drowning in PDFs, screenshots, and scattered emails. The AI Enquiry Builder ingests those mixed inputs and drafts a structured RFQ with lanes, package dimensions, incoterms, and due dates prefilled.
Result: buyers move from document collection to quote comparison in one sitting.
Supported inputs
- Supplier emails (EML/MSG copy or pasted text)
- Packing lists & POs (PDF/PNG/JPG)
- Mobile screenshots (WhatsApp, WeChat, etc.)
How it works
- OCR extracts text from PDFs/images.
- Parsing detects lanes, dims/weights, and shipment metadata.
- Prompting maps text to Logwo’s RFQ schema (fields you can edit).
- Review you confirm, tweak, and broadcast to vendors.
Example: transforming a packing list
// Extracted (simplified)
Origin: Shenzhen, CN
Destination: Dubai, AE
Packages: 12 cartons
Dims (cm): 60x40x35 each
Gross weight: 210 kg
Incoterms: EXW
Special: fragileBecomes a prefilled RFQ with origin/destination, package count, average dims/weights, and a “fragile handling” flag vendors must acknowledge.
Improving accuracy
- Prefer native PDFs over photos when possible.
- Include unit labels (cm/kg) to avoid ambiguity.
- Attach original docs — vendors can verify context.
Privacy & security
Documents are stored in tenant-scoped buckets. Access is time-limited via signed URLs. OCR output stays in your tenant; audit logs capture who uploaded and when.
What’s next
- Template memory for recurring vendors
- HS code hints from product descriptions
- Bid form prefill for invited forwarders