Introducing Chequedb: Bank-Grade Cheque Management, Now for Every Business
Banks have processed cheques with precision and auditability for decades. AI-driven validation, fraud detection, end-to-end lifecycle tracking, immutable audit trails—infrastructure most businesses assumed they could never access. Until now.
Chequedb is an AI-powered cheque management system built to deliver that same level of accuracy and control to any organisation that handles cheques. Accounting firms, property managers, insurers, manufacturers, distributors, professional services firms—if your business issues or receives cheques, Chequedb gives you the tooling that banks built for themselves, deployable in your environment, connected to the systems you already use.
Why "Bank-Grade" Matters for Business
When a bank processes a cheque, it isn't just scanning an image. It's extracting structured data, cross-referencing account records, applying validation rules, routing exceptions for human review, and building a time-stamped audit trail that stands up to regulatory scrutiny. Every field, every action, every decision is logged.
Most business cheque processes look nothing like this. Cheques arrive in the mail, get manually entered into a spreadsheet, and eventually reconcile—or don't—at month end. The gap between what banks do and what most businesses do represents a significant exposure: missed fraud signals, reconciliation errors, weak audit evidence, and time-consuming manual work.
Chequedb closes that gap. The platform applies bank-grade processing discipline to business cheque workflows, without the cost or complexity of building it in-house.
The Differentiator: Handwriting OCR That Understands How People Actually Write
Cheque amounts in the real world are not always written in textbook form. Payees write in shorthand. Regional conventions differ. Local colloquial expressions appear on cheques every day:
- "Twenty-five hundred" instead of "Two thousand five hundred"
- "One lakh fifty thousand" in South Asian markets
- "Fifteen hundred and 00/100" compressed onto a single line
- "$2.5K" written in the memo field as the intended amount
Standard OCR systems—trained on printed text—fail on these variations. They either misread the amount, return a low-confidence result, or flag the cheque for manual review unnecessarily.
Chequedb's handwriting recognition is trained on real-world cheque samples, including the colloquial and regional amount expressions that appear in everyday business banking. The system reads what was actually written, not just what should have been written. Cross-validation between the numeric figure and the written amount catches discrepancies early, before a cheque reaches your bank.
This matters especially for high-volume cheque processors—property management offices receiving rent payments, accounting firms handling client payments, insurers receiving premiums—where manual review of every handwritten amount is simply not feasible.
Full Cheque Lifecycle Management
Chequedb doesn't just capture cheques—it manages them through every stage of their lifecycle:
Capture and extract. Upload cheque images via the portal, mobile app, scanner SDK, or API. The AI engine extracts payee name, amount (numeric and written), date, MICR line, signature region, and any memo or reference fields. Confidence scores flag uncertain extractions for human review.
Review and approve. Route extracted cheques through configurable approval workflows. High-value items, low-confidence extractions, and policy-matched exceptions can all trigger specific review queues. Approvers see the original image alongside extracted data and can correct, approve, or reject in one screen.
Track status. Every cheque in the system carries a lifecycle state: received, under review, approved, deposited, cleared, returned, stopped, voided, or reconciled. No more hunting through bank statements to find out where a cheque stands.
Reconcile. Match cleared cheque records against bank statement data. Unmatched items surface automatically so your team can investigate rather than search.
Audit trail. Every action—view, extraction, correction, approval, export, status change—is logged with a timestamp and user identity. The trail is append-only and cannot be edited after the fact.
ERP and Workflow Integration
Chequedb is built to connect, not to exist as an island. The REST API exposes every object in the system—cheque records, extracted fields, approval decisions, status updates, audit events—so your existing finance infrastructure can stay in sync.
Common integration patterns:
ERP synchronisation. Push extracted cheque data (payee, amount, date, reference) into your ERP as it's validated. SAP, Oracle, Microsoft Dynamics, QuickBooks, Xero, Sage—any system with an API can receive cheque records from Chequedb without manual re-entry.
Approval workflow hooks. Trigger approval requests in your existing workflow tool when a cheque requires review. Webhook events fire when a cheque enters a queue, gets approved, gets rejected, or changes status—letting you connect Chequedb decisions to Slack, email, Microsoft Teams, or any approval engine you already use.
Accounting reconciliation. Export cleared cheque data in structured formats that slot into your month-end reconciliation process. Match by cheque number, amount, payee, or reference code.
Document management. Archive cheque images and audit trails to your document management system automatically. Maintain a single source of truth for compliance without duplicating effort.
For businesses with on-premises data requirements—financial institutions, regulated industries, government contractors—Chequedb deploys within your own infrastructure. The same AI capabilities run locally, with no data leaving your environment.
What This Looks Like in Practice
Property management office. A regional property manager receives hundreds of rent cheques each month from tenants across multiple buildings. Tenants write amounts in varying formats and handwriting quality ranges from printed to barely legible. Chequedb captures the batch via a desktop scanner, extracts every amount including colloquial expressions, flags any that don't match the expected rent amount, and routes exceptions to the relevant property manager. Cleared cheques post automatically to their property management software.
Accounting firm. A mid-size accounting firm handles client payments, supplier payments, and trust account transactions across dozens of client files. Chequedb provides a multi-client portal where each file has its own approval workflow and audit trail. The API exports validated payment data to the firm's accounting software. Auditors can pull the full event history for any cheque in seconds.
Insurance company. An insurer receives premium cheques by post from commercial policyholders. Policy numbers are written in the memo field, sometimes in non-standard formats. Chequedb extracts and normalises reference fields, matches them against the policy register via API integration, and flags any payments where the amount doesn't match the premium due. Exception queues route to underwriting staff rather than sitting in an unmonitored inbox.
Manufacturer. A manufacturer issues supplier payment cheques and receives customer payments. The finance team needs an audit trail showing who approved each payment, when it was issued, and when it cleared—for both internal controls and external audit purposes. Chequedb's maker-checker workflow enforces approval requirements by amount threshold and provides immutable evidence for the audit file.
Getting Started
Chequedb is available as a cloud deployment or on-premises installation. Setup for cloud deployments typically takes one to two days; enterprise and on-premises deployments with API integrations run two to four weeks depending on integration scope.
The platform scales from a small team processing a few hundred cheques per month to high-volume operations handling tens of thousands of items. Pricing is volume-based.
Book a demo to see the handwriting recognition, lifecycle workflows, and API integration in action with your own cheque samples. Or explore the API documentation if you're evaluating integration options.