Practical AI for the controller, the CFO and the close.
AI is finally useful inside a finance function — if it's implemented by someone who knows the close, the controls and the audit. Cagni Finance & Advisory designs and runs AI-assisted reconciliation, bookkeeping and CFO workflows that stay audit-ready.
AI where it earns its keep — not everywhere.
We map the workflow first, then pick the smallest AI or automation intervention that removes the most manual work. Every automated step ships with the audit trail, controls and human review your auditor expects — so speed doesn't cost you assurance.
Six AI-for-finance use cases we deliver.
- AI-assisted reconciliation: pattern matching across PSP, bank and ledger feeds
- AI bookkeeping: document parsing for invoices, receipts and bank statements
- AI CFO workflows: variance analysis, board-pack drafting and cash forecasting
- AI controller review: anomaly detection and exception routing on the close
- Python and low-code pipelines wired into NetSuite, Oracle, SAP or Xero
- Controls, audit trail and human-in-the-loop review on every automated step
Finance teams ready to move from spreadsheets to AI-assisted workflows.
Scale-ups and mid-market businesses whose close is still manual — where an AI controller layer, AI reconciliation or AI bookkeeping would compress days out of the month and free the team for judgement work.
Questions I get asked
- Where does AI actually help in finance?
- In the remainder: clustering reconciliation exceptions, drafting variance explanations, reading unstructured documents and summarising for management. The deterministic 95% should stay rule-based so auditors can reproduce it.
- Is it safe to put financial data into AI tools?
- Only with the right boundaries: approved vendors, no training on your data, data minimisation, and human review before anything posts. Those controls are designed as part of the engagement.
- Do we need new software?
- Rarely at the start. Most first wins come from better use of the ERP, close tool and spreadsheets you already pay for, with automation added where the volume justifies it.
- How do you measure the benefit?
- Close days, manual journal count, exception volume and hours spent per cycle — measured before the change so the improvement is not a matter of opinion.
- Will this replace finance roles?
- It removes the low-value work first. In practice teams keep their headcount and spend it on analysis, controls and business partnering instead of copying data.
AI for finance · start with a diagnostic.
30-minute call to map where AI and automation move the needle first — with the controls to keep it audit-ready.
30 minutes, no obligation. Bring your close timeline and top pain points.
Book a diagnostic call