Checks are scattered.
Invoice, PO and receipt data often sit in separate exports. A status or total alone does not tell a reviewer which row disagrees or why.
Accounts payable / Evidence-led reconciliation
Every discrepancy needs evidence.
Compare supplier invoices with purchase orders and goods receipts. Trace mismatches to source records and explicit rules—so finance teams can see what differs before deciding what to do next.
ILLUSTRATIVE DATA · NO CUSTOMER FILES REQUIRED
01 / INVOICEIN
INV-1003
HARBOR SUPPLY
ITEM PART-C20 × $9.00
PRICE REVIEW
02 / PURCHASE ORDERPO
PO-5003
HARBOR SUPPLY
ITEM PART-C20 × $8.50
PRICE DIFFERENCE
03 / GOODS RECEIPTGR
GR-7003
PO-5003 / PART-C
RECEIVED15 OF 20
SHORT RECEIPT
Illustrative records · inspect the runnable sample below
Evidence, not a black-box scoreEach finding points to source fields and the rule that triggered it.
Designed for AP reviewInspect exceptions, compare records and export a review worklist.
Browser-side sampleUploaded CSVs are processed locally in this version.
02 / Investigation
Follow the exception to its source.
Run the included sample or load your own approved CSV exports. Select any result to inspect the source values, matching rule and evidence trail. This demonstration runs in your browser.
Supplier invoicesSOURCE A / CSV
Invoice ID, supplier, PO reference, item, quantity and unit price.
Purchase ordersSOURCE B / CSV
PO line, supplier, item, ordered quantity and agreed unit price.
Goods receiptsSOURCE C / CSV
Receipt identifier, PO line, item and quantity received.
Sample records are preloaded. Run to produce the report.
03 / Who it serves
For finance teams that need to explain a mismatch—not just flag one.
Designed for accounts-payable leads, controllers, and finance operations teams reviewing supplier invoices against purchase orders and goods receipts. Most relevant where spreadsheet checks are repetitive and exceptions need a clear trail back to source rows.
One reviewable trail.
Compare configured fields, see the triggered rule, inspect source-row references and export exceptions for human review.
Assist review; do not replace it.
This is an early-stage workbench, not an ERP, payment approval system, audit certification or promise that every exception will be detected.
Why consider a test?
Choose it for inspectability—not for a claim we cannot yet prove.
- Rules and compared values are visible.
- Sample data can be reset explicitly.
- Results and exceptions can be exported for review.
- Scope, acceptance criteria and fee are agreed before paid work starts.
How a first client can find this
A clear sample earns attention. A relevant introduction earns the meeting.
This website is a proof point, not a lead-generation engine by itself. The realistic route is to show the working sample to AP leaders and finance operators, and build referral relationships with bookkeeping, finance-operations and ERP implementation consultants who already serve those teams.
- Show the evidence.Share the live sample and a short, role-specific explanation of the check it performs.
- Qualify the workflow.Confirm file formats, review pain, decision owner and what a useful test result looks like.
- Agree a paid test.Set scope, fee, timeline, data handling and acceptance criteria in writing before starting.
- Deliver proof, not promises.Return a findings report and exception CSV; review false positives and missed cases with the client.
Commercial path / no public price
01Scope
Agree checks, sample files, boundaries and acceptance criteria.
02Quote
Send a written fee and timeline. No fee is implied by this page.
03Payment
Use an agreed, legitimate invoice/payment route before the evaluation begins.
04Evidence
Deliver the report, export and review session specified in the agreement.
Initial evaluation should use synthetic or client-approved anonymized data. LedgerTrace does not yet claim production-grade security, ERP integration or guaranteed detection.
04 / Methodology
A finding should explain itself.
LedgerTrace applies explicit comparisons to the records provided. It does not infer intent, decide whether an invoice is fraudulent, or replace an AP review process.
Connect the source rows
Normalize identifiers and compare invoice lines with purchase-order and receipt rows using PO number and item code. Missing or ambiguous relationships must remain visible.
Show the rule and values
Flag configured conditions such as duplicate invoice IDs, supplier differences, price deltas, quantity excesses, missing receipts and unmatched source rows.
Keep the human decision
Inspect the evidence, record review notes and export the worklist. A finding is not a payment instruction, and opening it does not resolve it.
Current evaluation boundary
This is a static browser-based pilot, not production accounting software. It has no server upload, user accounts, saved cloud history, ERP integrations, payment actions, currency conversion, tax/credit-note treatment or robust split-line matching. Use synthetic or approved anonymized data and validate outputs against original documents.
05 / Paid evaluation
Test against a known answer—not a sales demo.
Define a bounded reconciliation problem first. Agree on inputs, supported checks, exclusions, deliverables, fee, timeline and acceptance criteria before any paid work begins.
The goal is to establish what the tool catches, what it misses, which findings are real, and whether the workflow merits further investment.
A human-reviewed reference set for comparison
Confirmed findings, false positives and missed exceptions
A traceable report and agreed review criteria
Scope and commercial terms agreed before work starts
Evaluation scope builderCONFIGURE / REVIEW / CONTACT
Step 01 / Source records
Step 02 / Checks to discuss
These are scope topics, not a guarantee that every check is fully supported in every data shape. Confirm edge cases and acceptance criteria before quoting.
Step 03 / Review the brief
Proposed evaluation briefDraft
Source types3 selected
Checks6 selected
DeliverablesFindings report + CSV
Commercial termsAgreed after scoping
No public price is shown because scope, data quality and validation effort determine the quote. No files are needed to start the conversation.