You're being asked to put AI and agents on top of the numbers. But AI only amplifies what you feed it: point it at fragmented PSP and settlement data and it scales the errors, faster. Before the copilots, you need one reliable source of truth. This free scan shows whether you have one, and what's still missing.
No data exports. Your answers stay private. No sales call. Built by a 13-year Deloitte Registered Accountant.
Most finance functions already run AI. Far fewer have the one thing it depends on: clean, reconciled numbers from a single source of truth.
Adoption has crossed the majority mark: 58% of finance functions were already using AI in 2024 (Gartner). Readiness has not kept pace. Sources: OneStream / PR Newswire, 2026 · Gartner AI in Finance Survey.
High-volume finance teams almost always overrate their own maturity. [Add a real stat here, e.g. 7 in 10 score below Level 3.] The only way to know your number is to measure it. Twelve minutes, scored against your peers.
Get your score →Point a model or an agent at fragmented PSP and settlement data and it won't flag the gap. It builds on it, confidently, and hands you a wrong answer faster than any human could.
In the same research, the executives making the most decisions on faulty data were the heaviest AI users. More tools on a shaky foundation is more exposure, not less.
That is why a single source of truth isn't a nice-to-have for AI. It's the precondition.
Feed AI the truth and it compounds.
Feed it guesses and so do the errors.
Why pre-accounting control comes before the copilots
AI-ready finance data has structure. The same six factors that decide your financial control are exactly what a model, agent or copilot needs underneath it: validated at the source, traceable end to end, current, self-explaining, provable, and built to scale. The scan measures all six.
The volume isn't slowing down. Hiring your way out just moves the ceiling up a floor. Real financial control is structural, established before the ledger, or it isn't control at all.
Together, these six are your single source of truth: the foundation any AI has to run on. Each builds on the last, so a gap early on quietly poisons everything downstream, automated or not.
Is truth established before data enters the ERP?
SOURCE measures whether you validate transactions at origin, before they contaminate everything downstream.
Can every transaction be traced source to journal?
TRACE measures whether you have one connected, auditable trail across all systems, not tribal knowledge.
Do you know where you stand daily, or only at close?
PULSE measures the frequency and reliability of your financial visibility. Steering, not month-end guessing.
Does the system explain why differences exist?
ROOT measures how much variance analysis is automated, versus people rediscovering the same issue every month.
Can you prove completeness at any moment?
PROOF measures whether audit readiness is structural, a byproduct of daily operations, or an annual fire drill.
If volume doubled tomorrow, would it hold or break?
SCALE measures whether infrastructure absorbs growth without proportional headcount. Scale without heroics.
SOURCE → TRACE → PULSE → ROOT → PROOF → SCALE. A chain is only as strong as the factor that breaks first.
The instinct is to start with the model. The leverage is the other way around. Establish one reconciled, validated source of truth first, and every AI use case on top of it compounds value instead of errors.
For most high-volume teams the gap is right at the start: data is never validated before it enters the ERP. Close that, and your numbers become something a model can actually trust. The scan pinpoints your earliest gap, so you fix the foundation, not the symptom.
Both feel like control from the inside. Only one survives 2× volume and a sharp auditor.
“We thought we were audit-ready. The scan found two PSP flows that never tied out. We fixed them before our raise, not during it.”
[Name, CFO] · [Company] · replace with a real, approved quote
From four FTE on reconciliation to one, without slowing the close.
Proof-of-concept to working trace in days, not a quarter-long project.
From waiting a month for reporting to live financial visibility, mid-month.
Real control doesn't mean checking more. It means building a system that doesn't need to be checked.Peter EngelFounder & CEO, Actuals · 13 years as a Public Registered Accountant & Auditor at Deloitte
Actuals builds the pre-accounting control layer for high-volume finance teams: a single source of truth across order, payment and settlement data, before it ever reaches the ledger. Because accounting truth doesn't originate in the ERP. It originates before.
Answer focused questions about how your high-volume finance setup actually works today. No prep, no data exports.
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Optional, no-pitch conversation about your Real Financial Control roadmap and where the chain breaks first.
