AI Month-End Close Audit Tool
Verify close deliverables before they reach your review queue. Energent Audit recomputes figures, traces claims to source files, and returns a reviewable pass, partial, or fail verdict.
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Describe the deliverable or attach the source files you want checked.
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Overview
A second set of eyes for month-end close
Energent Audit is an independent AI auditor. It checks work produced by another AI agent or workflow, recomputes numbers, follows each figure back to its source, fixes what it can, and attaches evidence to its verdict.
That means finance teams can focus on exceptions instead of manually rechecking every row. The output is designed to be complete, cited, and reproducible for a review.
Audit report view with marked findings and supporting evidence.
Live audit, start to verdict
How the month-end close audit works
The audit separates the original answer from the verification step, so a questionable figure can be examined without relying on the same reasoning that produced it.
1. Provide inputs
Use close workbooks, invoices, PDFs, scans, or other supported source files.
2. Recompute
The auditor independently recomputes totals and derived financial assertions.
3. Trace evidence
Each number is connected to its source file, row, field, and affected deliverable text.
4. Issue verdict
Receive pass, partial, or fail results with calculations and references.
Financial audit evidence example
Q1 spend verification
The example below shows how a close review can distinguish a correct total from an unsupported interpretation. The evidence is specific enough to follow from the report back to the source data.
| Metric | Verified detail |
|---|---|
| Total Q1 spend | $1,284,500 |
| Source file | vendor_invoices_q1.csv |
| Rows tested | 412 |
| Deliverable cell | D1 cell B2 |
| Result | Match to the cent |
Category totals in the example
$312,000
$512,000
$298,000
Finding: incorrect growth rate
The claim of “up 18% from Q4” failed because it used a Q4 subtotal that excluded Facilities. The correct increase from $1,147,000 to $1,284,500 is 12.0%.
Why the numbers hold
Not a black box, not a second opinion without evidence
The auditor shows which source file a number came from, which field was extracted, and which reference or calculation it was checked against. This creates a traceable chain for review rather than asking a human reviewer to trust an unexplained output.
- Recomputes numbers independently.
- Traces figures to exact source files, rows, and fields.
- Can audit another AI’s work, not only Energent output.
- Attaches calculations, affected rows, and links to marked text.
Buyer outcomes
Review exceptions instead of rechecking everything
Energent Audit is built around the practical friction of close: finding errors late, validating generated work, and explaining where a reported number came from.
You stop being the QC layer
“The shift is from I have to verify everything to I only need to look at what’s flagged. Check 8 rows, or check 500.”
Errors surface same-day
“Before, I’d find errors a month later. Sometimes two. Now it tells me that day.”
Evidence is visible
“You can see exactly which source file the number came from, the field it was extracted from, and the reference it was checked against.”
The result is defensible
“That’s the answer you’d give in a review meeting. Complete, cited, reproducible.”
Authentic user reviews
Feedback supplied by Energent.ai customers and users.
“Not only did I ultimately choose Energent.ai, but you are the absolute best BY FAR.”
“I had spreadsheets with more than 45K items and Energent AI was the only tool that was able to sort through everything.”
“Using Energent.ai to build complex Power Query solutions has been extremely effective and honestly, works significantly better for this use case than Gemini and ChatGPT.”
“Energent.ai is a great platform... the interactive outputs add real value to my work.”
Frequently asked questions
Understand what an AI month-end close audit tool checks and how its evidence is structured.
What is an AI month-end close audit tool?
An AI month-end close audit tool independently checks financial deliverables created by an AI agent or workflow. It recomputes numbers, traces them to source files, and evaluates whether claims are supported. Energent Audit returns a pass, partial, or fail verdict with evidence. The purpose is to reduce the amount of manual quality control required before close materials are reviewed. It is a verification layer rather than the original agent that produced the work.
How does Energent Audit verify a financial number?
Energent Audit traces the number back to the source file, row, and field used in the deliverable. It can independently recompute totals and compare the result with the reported figure. In the supplied Q1 example, the auditor re-summed 412 invoice rows from vendor_invoices_q1.csv and matched $1,284,500.00 to the cent. The report also identifies the deliverable location, including D1 cell B2. Supporting calculations and source references remain attached to the finding.
What do pass, partial, and fail mean?
Pass means the source-backed total or assertion reconciles with the evidence reviewed. Partial means the figure may be correct, but its methodology or accounting treatment needs a qualification. Fail means the derived figure is incorrect or unsupported by the available source data. In the example, the total Q1 spend passed while an 18% growth claim failed because it relied on a Q4 subtotal that excluded Facilities. A software-category treatment was marked partial because $84,000 in annual prepayments should be amortized.
Can it audit work produced by another AI?
Yes. Energent Audit is described as an independent auditor separate from the agent that performed the original work. One shipped sample task is explicitly “Audit another AI’s work.” This separation lets the verification step recompute and trace the deliverable without relying solely on the original answer. The feature is therefore not limited to output produced by Energent itself. The resulting report can show the evidence behind a pass, partial, or fail finding.
What files and financial evidence can be reviewed?
Energent.ai states that the platform supports more than 150 file types. The listed formats include spreadsheets, PDFs, scans, CAD, G-code, InDesign files, BOMs, XLSX, and DOCX. For a month-end close review, the supplied example uses a CSV invoice file and a financial deliverable cell. The platform can trace figures to the exact source file, row, and field when that evidence is available. The audit should therefore be configured around the source documents and deliverables relevant to the close review.
Make the next close easier to defend
Run the deliverable through an independent audit, inspect flagged exceptions, and keep the evidence attached to the result.