The problems you already know about
Finance teams spend most of their day on data entry and reconciliation. AI takes those tasks off the floor without breaking your audit trail.
AP and AR teams drown in invoices
Every invoice gets opened, retyped, classified, approved, and filed. Per-invoice cost stays high regardless of volume. Senior accountants spend their day on data entry that a junior could (and should) automate.
AI extracts vendor, line items, GL codes, and approval routing from invoices in any format (PDF, image, email body). It feeds your AP system directly. Your team reviews exceptions instead of typing every line.
Reconciliation breaks at scale
Bank, card, payment processor, marketplace, ERP. Five sources, different formats, different timing. Manual matching works at small volume and falls apart as the business grows.
AI matches transactions across systems with deterministic rules first, then LLM-assisted matching for the ambiguous cases. Every match is logged with reasoning. Unmatched items go to a human queue with suggested matches ranked by confidence.
Month-end close takes too long
Accruals, intercompany, FX, journal entries. The close cycle compresses everyone for a week, every month. Errors caught late require reopening books. CFO reporting waits.
AI pre-stages accruals and intercompany entries from source data. It flags anomalies before they hit the ledger. Close days drop because the manual prep is already done.
Audit requirements add friction
Every AI decision needs a paper trail. Generic AI tools give you outputs without provenance, which makes auditors nervous and compliance officers slower.
We build audit-grade logging into every step. What the AI saw, what it decided, why it decided it, and who approved it. Auditors get a queryable trail; your finance team gets faster sign-off.
What to measure in a finance pilot
Measurement examples, not client averages or guaranteed results. Establish the finance team's baseline and acceptance thresholds before rollout.
How it works
We profile your finance operations
Volume by document type, error sources, exception patterns, and system landscape (ERP, AP/AR, treasury, banks). We select a first workflow by measurable value, evidence quality, implementation complexity, and risk.
We build with audit in mind from day one
Every AI decision is logged with input, output, confidence, and reasoning. We design for auditor review, not against it. Eval harness includes adversarial test cases (edge invoices, ambiguous reconciliations).
You see cycle time drop, not headcount
Most finance teams use AI to grow capacity rather than cut roles. Senior staff stop typing data and start analysing it. That is where the real ROI comes from.
Free tools to get started
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Common questions
Is this safe for regulated finance work?
Safety depends on the workflow, materiality, jurisdiction, data handling, and control design. Deterministic rules should handle known high-stakes paths, with AI assisting on bounded ambiguous work and people reviewing material or uncertain cases. Involve finance, security, compliance, and assurance owners before rollout.
Will AI catch errors a human would miss?
It can surface duplicates, mismatched line items, and unusual coding patterns, but performance depends on the data and controls. Test these cases against a representative evaluation set, keep deterministic checks for known rules, and route uncertain or material items to human review. Duplicate and anomaly review of this kind also runs in claims work, described in AI for insurance brokers.
Which finance systems do you integrate with?
NetSuite, QuickBooks, Xero, Sage Intacct, SAP, Oracle Fusion, and most major ERPs via API. AP automation tools (Bill, Tipalti, Coupa, Ramp) integrate cleanly. We also work with custom-built internal finance systems. Practices running client ledgers on these systems can start from AI for accountants and accounting firms.
How long until we see ROI?
That depends on transaction volume, current handling time, exception rate, integration cost, and the amount of review the workflow needs. Baseline those inputs before building, then compare operating cost and correction work during a controlled pilot. We do not promise a universal payback period. You can sketch the inputs first with our AI ROI calculator.
Will our auditors accept this?
Acceptance depends on your auditor, jurisdiction, materiality, and control design. Involve them early and provide process documentation, evaluation results, decision logs, exception-handling procedures, access controls, and human-review checkpoints for assessment. Reviewing an existing workflow against those requirements is the purpose of AI audit and hardening.
Cut close-cycle time. Keep your audit trail.
Book a free 15-minute call. We will scope which finance workflow offers the clearest, safest first pilot in your operation.