JobBridge: AI Bank Reconciliation & Finance DLP

Every job-based SME — facilities management, construction, logistics, professional services — runs the same manual chain: jobs are completed in the field, someone compiles the data, someone drafts an invoice in Xero or QuickBooks, and then someone reconciles incoming payments against those invoices line by line on the bank statement. Every step is human, and the final one touches the most sensitive data the business holds — customer names, account numbers and amounts.

Off-the-shelf tools each own one slice and stop. Xero and QuickBooks bill but wait for human input. Field-service platforms like Simpro and ServiceTitan capture jobs but cost SGD 200-400/month with no Singapore compliance — and none of them reconcile the bank statement. Teams that tried to automate reconciliation with AI hit a wall: matching transactions reliably needs a capable model, but feeding raw bank statements to an external AI means confidential financial data leaving the business, which is a non-starter under PDPA.

What nobody had was a lightweight, Singapore-context engine that takes a job from completion to a drafted invoice and then reconciles it against the bank statement automatically — without that confidential data ever leaving the company's own infrastructure in the raw.

JobBridge is a Job Card → Auto-Draft Invoice → Bank Reconciliation engine. Field staff capture job completion data on mobile in under 90 seconds — GPS-verified start and end times, photos, signatures and materials usage, all from their phone. No paper, no WhatsApp messages to compile later.

On completion, the system drafts an invoice and pushes it to Xero or QuickBooks via API; the human only reviews and approves. It supports progress billing for construction subcontractors and SLA-based billing with breach alerts for facilities management, and an optional client portal lets customers check job status themselves instead of calling.

At the reconciliation step, an AI engine reads the bank statement and matches each transaction against the open invoices in seconds, surfacing only the exceptions a person needs to look at.

Because reconciliation runs on confidential financial data, none of it reaches the external model in the raw. Every capture passes through a secured layer that runs entirely on the client's own infrastructure — classifying sensitive fields on-device, redacting and tokenising identities reversibly, and sending only sanitised, structurally-intact data to the AI. The section below shows exactly how that works, and what the model actually receives.

Pricing starts at SGD 199-399/month for up to 10 field staff — accessible for small teams that can't afford enterprise field-service tools.

The model parses structure — amounts, dates, layout — to reconcile. Identities never leave. Tokens are restored in-memory when the response returns; the map is never persisted or logged.