Payables consume administrative hours
Invoices are opened, coded, matched and keyed in one at a time, and errors surface at month end.
Solutions · Finance & administration
Finance is full of high-volume, rule-bound document work — and it is also where an unreviewed automated action does real damage. We build for both: the throughput of automation, with approval gates before anything is posted or paid.
The problem
Invoices are opened, coded, matched and keyed in one at a time, and errors surface at month end.
Renewal dates, notice periods and terms exist only in contracts nobody re-reads until it is too late.
Mismatches between systems are discovered during close instead of when they occur.
What we build
Every one of these is described as a business workflow, not an AI feature. Each is scoped, measured and deployed the same way.
Invoice processing
Invoices read, coded, matched and queued for approval instead of keyed in line by line.
Expense organization
Receipts and expenses categorised and reconciled against policy as they arrive.
Document classification
Incoming paperwork identified, named, filed and made findable.
Contract summaries
Key terms, dates and obligations extracted so nothing important lives only in a PDF.
Payment reminders
Receivables chased consistently and politely, on a schedule, with escalation rules.
Data reconciliation
Mismatches between systems detected and flagged rather than discovered at month end.
Management reporting
The finance pack assembled from source systems on a fixed cadence.
Administrative workflows
The recurring admin nobody owns, given a defined process and a monitored owner.
Worked example
A described workflow pattern, not a published client deployment. Scope, systems and measurement are confirmed for your business during the AI Opportunity Roadmap.
Questions
It is safe when the AI prepares the entry and a person approves it, which is how we build it. The system reads the invoice, codes it against your chart of accounts, matches it to a purchase order and places it in an approval queue. It does not post to the ledger and it does not release payment. That approval gate is not optional in a finance build — the throughput gain comes from eliminating data entry, not from eliminating review.
Accuracy is high for standard fields such as supplier, date, total, tax and line items on typical business invoices, and lower for unusual layouts, handwriting, poor scans and non-standard tax treatments. The right way to answer this for your business is a measured baseline: during a Value Sprint we run representative documents from your actual supplier mix and report the real extraction accuracy before anything goes into production.
Yes. Key terms, dates, notice periods and obligations can be extracted from contracts into a tracked register with reminders ahead of each deadline. Because the consequence of a missed or misread term is high, extracted terms are confirmed by the contract owner before the register is relied upon — the AI removes the reading and re-keying, not the responsibility.
Mainstream accounting and ERP platforms expose the APIs needed to read purchase orders and write draft entries, so in most cases yes. The software and integration review in the AI Opportunity Roadmap confirms it for your specific system and plan tier — including whether the API supports draft entries pending approval, which some do not — before implementation is quoted.
Related
Lead intake · Lead qualification · Personalized follow-up
Customer serviceInquiry classification · Response assistance · Request routing
OperationsWorkflow automation · Document processing · Task routing
MarketingResearch · Content workflows · Customer segmentation
Get started
Show us where your business is losing time, revenue, capacity or visibility. We will help determine whether AI can solve it — and what the first practical step should be.
hello@askgeeks.ai · Vancouver, BC · remote across Canada & the US