Expense management & reconciliation

Track expenses.
Reconcile with confidence.

LedgerMatch is a multi-user expense management platform with an integrated reconciliation engine. Import transaction CSVs, normalize records, and match them across two sources using rule-based confidence scoring.

Multi-user workspaces
CSV import pipeline
Rule-based reconciliation
Confidence-scored matching
ledgermatch.app/dashboard
Dashboard
Expenses
Imports
Reconciliation
Categories
Accounts

Spend this month

$8,432

Spend this week

$1,240

Pending review

4

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Built for real expense workflows

Everything you need to manage, import, review, and reconcile business expenses — without the complexity of enterprise finance software.

Full expense management

Add, edit, and categorize expenses manually or from imports. Filter by date, category, account, and status. Every expense ties back to a category record — renaming a category never orphans your data.

CSV import pipeline

Upload any bank export or expense report CSV. Map columns to expected fields, preview the parsed data, normalize rows, and optionally convert them directly into expense records.

Rule-based reconciliation

Compare two import sources side by side. The matching engine scores suggestions based on amount, date proximity, and description similarity. Accept, reject, or manually link each pair.

Workspace categories

Create custom categories with colors. Archive categories gracefully — existing expenses retain their history, and you can reassign records before archiving.

Dashboard insights

Monitor monthly and weekly spend, category breakdowns, recent transactions, and a live reconciliation review queue — all on a single, information-dense dashboard.

Multi-user workspaces

Each user gets their own workspace with role-aware data isolation. Owner, admin, and member roles keep team data clean and secure from day one.

How it works

From CSV upload to reconciled output in four steps

1

Upload your CSV files

Export a bank statement or expense report as CSV and upload it. Map your column headers to the expected fields — LedgerMatch will auto-detect common patterns.

2

Normalize and review

Each row is parsed, validated, and normalized into a structured record. Optionally convert imported rows into expense records with a single click.

3

Run reconciliation

Select two import sessions and run the matching engine. It scores candidate pairs by amount, date, and description similarity — then queues them for your review.

4

Accept, reject, export

Review each suggested match. Accept matches you agree with, reject false positives, and manually link any unmatched rows. Export cleaned results as CSV.

Ready to reconcile smarter?

Create a free account, upload your first CSV, and see your matches in minutes.

Demo credentials: alice@example.com / demo1234