Review total
Grand total $52,300 · math mismatch
Line-item sum $48,750 · difference $3,550
Container MSCU1234565 · check digit valid
Auto-pass
Consignee matched against shipment packet
Vessel / voyage consistent across pages
ROUTING DECISION
2 safe fields auto-pass. 1 risky total stops for review with evidence.
The real risk
Poor-executed document workflow is what hurts your operations.
Teams re-key documents because extracted data is not trusted enough to flow downstream automatically. The larger problem is a single bad field creating a clearance delay, billing dispute, denied claim, compliance issue, or rework loop.
Clearance delay
A mismatched total, missing party, or invalid container value stalls the shipment.
Billing dispute
Wrong quantities, prices, totals, or currencies become downstream exceptions.
Denied claim
A smudged member ID or missing intake field can quietly break the workflow.
Manual rework
Ops teams find the error later, then restart the same document loop.
Compliance issue
The document did not add up, but the system accepted the value anyway.
Customer escalation
The customer sees the exception before your team catches the bad field.
How it works
From messy document intake to trusted system-ready records.
Our solution sits between incoming operational documents and the systems that depend on them. It extracts the fields, checks the values, routes uncertainty, and keeps learning from every exception your team resolves.
01
Ingest
Bring in invoices, BOLs, packing lists, customs paperwork, and shipment documents in the formats your vendors actually send.
02
Extract
Pull workflow-specific fields and keep source evidence so your team can see where each value came from.
03
Verify
Check totals, dates, required fields, container IDs, duplicates, and cross-document consistency before anything moves downstream.
04
Route
Send risky fields to review, capture the resolution, and turn repeated exceptions into stronger operational rules over time.
Send one painful document workflow.
We’ll run the full end-to-end process on your real documents and show what can safely auto-pass, what needs review, and what clean output would look like.
Beyond OCR
OCR confidence is not operational confidence.
OCR asks: Can I read the text?
A high OCR score can still miss the business problem: wrong total, wrong shipment, duplicate invoice, missing customs field, or a value that does not match the rest of the file.
Our System: Is this safe to use?
We turn operational failures into rich context checks: totals against line items, invoice against BOL, shipment against vendor history, exceptions against SOPs, and reviewer fixes against future rules.
Where & When We Need AI
AI can understand messy context across systems.
In 2026, the advantage is not replacing every rule with AI. It is using AI to connect documents, infer operational context, learn from exceptions, and improve the workflow — while deterministic checks still enforce what must be exact.
Loop 01 · Reduce manual review
Find the facts operators hunt for
AI pulls invoice totals, parties, references, currencies, line items, and shipment signals so your team spends less time reading PDFs and more time clearing exceptions.
Loop 02 · Catch costly mismatches
Match documents before errors spread
Link invoices, BOLs, packing lists, and shipment references even when vendor formats differ. Flag duplicates, missing records, and conflicts before they hit TMS, billing, or clearance.
Loop 03 · Improve over time
Turn reviews into better rules
When your team fixes an exception, this solution captures the reason and suggests where the workflow can safely auto-pass next time.
Non-AI layer · Keep trust high
Use rules where AI adds no value
Totals, required fields, dates, container check digits, currency normalization, and audit rules stay deterministic — so the system is fast, explainable, and dependable.
Proof example
One system files the invoice. Skyline.Dev catches the business risk.
A commercial invoice arrives with 12 line items and a printed grand total of $52,300. The line items only add up to $48,750. Our solution catches the $3,550 mismatch before that value enters the downstream system.
Printed total
$52,300
Line item sum
$48,750
Difference
$3,550
Container number
Invoice total
Best-fit customers
For logistics and customs brokerage teams buried in operational documents.
High-volume document operations
For teams processing commercial invoices, bills of lading, packing lists, freight invoices, customs paperwork, shipment documents, and related references all day.
Best-fit signals: back-office teams re-keying data, clearance delays tied to document errors, vendor formats that constantly change, and a high cost for a single wrong field.
Customs brokerage validation
Skyline.Dev checks the fields that matter before values reach your TMS, clearance workflow, billing system, or claims process.
Common checks: invoice total vs line-item sum, container number check digit, required fields, date validity, party names, shipment references, currency normalization, and duplicate or conflicting fields.
Pilot Engagement
End-to-end experience.
Controlled scope.
Both pilots let your team taste the full loop: documents in, trusted fields out, risky fields routed, clean data exported.
Pilot I
Starter Workflow
For one painful document type and a small controlled test batch.
✓
1 document type
✓
100–200 real documents
✓
10–20 target fields
✓
3–5 validation checks
✓
Field-level trust scoring
✓
Exception routing
✓
Clean CSV / Excel / JSON output
Start Pilot I
Pilot II
Expanded Workflow
For a stronger production signal across two related document types.
✓
2 document types
✓
200–500 real documents
✓
20–40 target fields
✓
5–10 validation checks
✓
Cross-document consistency checks
✓
Exception review workflow
✓
Production handoff plan
Start Pilot II
