Documentation
Welcome to ScanLedger docs
ScanLedger is an AI-powered business data platform that unifies document capture, inventory, point of sale, bank reconciliation, and analytics into one product. These docs cover how every feature works, end to end.
What is ScanLedger?
ScanLedger is built for shop owners, operators, and accountants who want one platform instead of five. Every document scanned, sale processed, or statement reconciled becomes structured, searchable data that your whole team can work with.
- Capture. Photograph or upload any receipt, invoice, or handwritten note and get structured data back in seconds.
- Analyze. Turn captured data into datasets you can filter, chart, and chat with.
- Operate. Run your inventory, POS, and bank reconciliation on top of the same data.
How to use these docs
Pick a topic below — each page covers one feature in depth, with how-it-works concepts, step-by-step instructions, plan limits, and troubleshooting.
New to ScanLedger? Start with the Quickstart. Already signed up? Jump straight into the area you care about.
Quickstart
Scan your first document and explore the dashboard in 5 minutes.
Document scanning
How OCR works, supported formats, confidence scores, and batch uploads.
Document templates
Reusable structures with typed fields, layouts, stamps, and PDF/DOCX export.
Datasets
Schema-aware tables with filters, stats, search & replace.
AI chat
Ask natural-language questions against your datasets.
Inventory
Products, stock movements, low-stock alerts, and reports.
Point of Sale
Sell, manage receipts, split payments, and void workflow.
Shifts
Staff shifts tied to POS with cash reconciliation.
Bank reconciliation
Match statements to receipts, invoices, and sales — no bank API required.
Expected payments
Track what is owed and match it to incoming deposits.
Folders & files
Organize files and search with semantic AI.
Team & permissions
Roles, workspaces, and activity tracking.
Billing & plans
Paystack, Stripe, proration, and scheduled downgrades.
Security
Encryption, auth, AI data handling, and responsible disclosure.