FreightGraph AutoFill reads emails, PDFs, scans, images, and freight documents, extracts the information your operation needs, validates the results, and sends structured data into your existing systems.
Freight data arrives before your systems can use it.
Freight information is trapped in emails, PDFs, scans, images, and customer-specific documents. Before your team can act on it, someone has to read it, interpret it, and type it into a system manually. That translation step costs time at every stage of the operation.
Load assignments, carrier coordination, and customer updates depend on data that is still inside an unread document. Every hour that document sits unprocessed is an hour the operation runs without complete information.
Invoices cannot go out until PODs are processed, charges are confirmed, and accessorials are recorded. When documents move through people rather than systems, billing cycles stretch longer than they need to.
Manual retyping introduces mistakes that travel downstream. A transposed reference number or a missed accessorial charge creates disputes, redelivery costs, and reconciliation work that takes longer to fix than it took to create.
As volume increases, the document queue grows proportionally. Adding capacity means hiring more people to repeat the same process. The workload scales with the business and manual entry scales with it.
AutoFill receives a document, maps its content to configured freight fields, routes only exceptions for review, and delivers approved data to the destination workflow.
Bring documents into AutoFill through the intake channel configured for the workflow, such as an inbox, upload, scan, or system connection.
AutoFill identifies the document type and maps its contents to the standard or custom fields defined for that workflow.
Validation rules determine what can continue automatically and which missing, conflicting, or uncertain fields need a person’s attention.
After approval, AutoFill sends the mapped values to the connected workflow so the receiving system can create or update the appropriate record.
Standard freight fields, customer-specific references, internal codes, and custom identifiers can be mapped to the destination record. The example below shows the types of data a BOL workflow may be configured to capture.
Basic text recognition converts document images into raw text. AutoFill goes further, applying freight-specific understanding, structured extraction, and business-rule validation so the output is ready for your systems rather than just readable.
The document image is converted into machine-readable text. Characters are identified but not yet organized by meaning or field.
Text recognition
AutoFill identifies the document type: BOL, POD, rate confirmation, invoice, load tender, or other freight document. Classification determines which extraction rules apply.
AutoFill
AutoFill identifies specific freight data fields using models trained on logistics documents. It understands freight context rather than matching fixed templates.
AutoFill
Extracted fields are checked against your business rules. Exceptions are flagged for review. Approved data is delivered as structured output ready for system ingestion.
AutoFill
Each deployment can be configured around one or more document-driven workflows. The goal is not to automate every document at once, but to remove the highest-value manual bottleneck first and expand from there.
Manage queues containing several freight document types while applying the correct field requirements and routing rules to each one.
Capture shipment details split between an email body and its attachments without forcing staff to reconcile the message manually.
Make shipper, consignee, commodity, weight, reference, and charge data available for downstream operational records.
Move delivery confirmation, timestamps, signatures, exception notes, and condition details into billing and customer-service workflows sooner.
Keep agreed rates, accessorials, carrier details, and load terms connected to the record used by operations and billing.
AutoFill can map approved values to the fields, records, and workflows used by your existing systems.
Your team keeps working in its existing operating environment. AutoFill handles the document-to-record step according to the workflow, permissions, and controls agreed during implementation.
Transportation Management System (TMS)
Warehouse Management System (WMS)
ERP and accounting workflows
CRM and customer platforms
Document management systems
Custom platforms and databases
AutoFill applies confidence thresholds and business rules before data moves downstream. Clean fields can continue automatically. Missing, conflicting, or uncertain values are held in the same exception box, where a reviewer can compare the extracted value with the source and correct only what needs attention.
Each value includes a confidence indicator so reviewers immediately know where attention is required.
Choose which fields may continue automatically and which always require confirmation.
Keep the original document visible while correcting a flagged value instead of rereading the entire file.
AutoFill is designed for operations where incoming document volume is high, manual entry time is a measurable cost, and data accuracy affects billing, compliance, or downstream decisions.
Process rate confirmations, BOLs, and PODs from dozens of carriers and customers without building a manual entry team to keep pace with load volume.
Capture load tender details, delivery confirmations, and accessorial information from customer documents in the formats customers actually send them.
Process inbound carrier documents, PODs, and invoices into internal systems without maintaining a dedicated team to handle document intake and data entry.
Handle varied document types across multiple carrier and customer relationships. AutoFill adapts to the specific document formats your partners send rather than requiring them to change.
Embed AutoFill document intelligence into existing logistics platforms to add structured freight data capture without building extraction from scratch.
When freight documents are processed automatically rather than manually, the impact shows up across the operation. These are the areas where teams consistently see change.
The time your team spends moving data from documents into systems is reduced. That time is available for higher-judgment work the operation actually needs.
Load assignments, customer notifications, and carrier coordination can move forward as soon as a document is processed rather than waiting for someone to open and retype it.
Errors introduced by manual retyping are removed. Reference numbers, charges, and addresses flow from the source document to the system without a human typing step in between.
When PODs and rate confirmations are processed as they arrive, the data needed to generate invoices is available sooner. Billing cycles start earlier and disputes are easier to resolve with complete records.
Document volume can increase without a proportional increase in the team responsible for entry. Growth in load count does not automatically mean growth in manual processing work.
Structured freight data that reaches your systems accurately becomes searchable, reportable, and usable for analysis. Rate trends, delay patterns, and carrier performance become visible when the underlying data is clean.
AutoFill is implemented by workflow rather than all at once. Starting with the document type that creates the most manual work gives your team a clear result to evaluate before expanding.
Identify the document type that generates the most manual entry time. BOLs, PODs, rate confirmations, and invoices are common starting points.
Confirm the specific fields your operation needs to capture and which systems will receive the structured output.
Run actual documents from your operation through AutoFill to confirm extraction accuracy before going live with the workflow.
Evaluate extraction quality across your document formats and configure validation rules and approval thresholds that match your operation.
Once the initial workflow is running and validated, add additional document types, source channels, or system destinations based on operational priority.
Show us the documents your team receives, the information you need to capture, and the system that information needs to reach. FreightGraph will help map the path from incoming freight information to structured, usable data.