Catch quiet hallucinations
AI errors often look plausible rather than obviously wrong. Energent Audit independently checks the deliverable before it reaches a stakeholder, helping surface failures that may otherwise appear only in a later review.
Energent Audit for finance and FP&A teams
AI Audit for FP&A Reports Without Becoming the Quality-Control Layer
Energent Audit independently recomputes report numbers, traces figures to their source files, and returns a reviewable pass/fail verdict before an FP&A deliverable reaches stakeholders.
3×
Fewer hallucinations in public evaluations
150+
Supported file types
94.4%
Published leaderboard accuracy claim
100k+
Clients worldwide
Trusted by 100k+ companies across the globe.
A practical answer to AI reporting risk
The useful shift is from checking every row yourself to reviewing the rows and assertions that an independent auditor flags. That makes a report easier to explain, reproduce, and defend.
What Is AI Audit for FP&A Reports?
AI audit for FP&A reports is an independent verification process for forecasts, budgets, financial analysis, and other deliverables produced with AI or automation. Energent Audit acts as a second agent separate from the system that performed the original work. It recomputes numbers, traces figures to the exact source file, row, and field, checks assertions against source evidence, fixes issues where possible, and provides a pass/fail verdict with supporting evidence. For teams building a broader financial AI audit workflow, the purpose is not to remove professional judgment; it is to make review more focused and traceable.
Where Energent Audit Helps FP&A Teams
Each card represents a distinct outcome described in the supplied Energent Audit material.
Trace every number
The audit trail connects a figure to its source file, row, field, and reference used for checking. This creates a cited chain that can support a review conversation instead of leaving the result as a black box.
Review pass/fail results
The auditor issues a clear verdict and attaches evidence. Instead of treating every row as equally risky, the reviewer can focus on what was flagged and examine the underlying support.
Audit another AI’s work
The audit is not limited to Energent’s own output. One shipped sample task is “Audit another AI’s work,” making the approach relevant when FP&A teams use several AI systems or automation tools.
Turn corrections into repeatable controls
Energent describes reusable workflows that learn audit rules over time. In a recurring reporting process, a correction can become a persistent rule rather than a one-off note that disappears after the current reporting cycle.
A Live Audit, Start to Verdict
The operating model is deliberately separate from the original AI task. A report is submitted, the independent auditor checks its logic and evidence, and the result is returned as a reviewable decision rather than an unsupported confidence score.
This approach complements AI output audit trails by keeping the source evidence visible alongside the conclusion. The same principle applies across spreadsheets, PDFs, scans, CAD files, and other supported formats.
A full dashboard view can combine source-grounded analysis with visual summaries.
What You Get
The benefits below focus on the practical work of preparing and defending FP&A reports.
Review flagged work first. Shift from checking everything to examining the rows and claims the audit identifies.
Recompute reported values. Test whether numbers hold when independently recalculated.
Trace source evidence. Follow figures back to the source file, row, and field used to support them.
Surface errors the same day. Identify issues during delivery rather than waiting for a later reporting cycle.
Support defensible reviews. Use complete, cited, reproducible evidence in review meetings.
Reuse audit rules. Turn recurring corrections into workflow controls that can persist over time.
How It Works
Step 1
Submit the deliverable
Provide the report and its source material, including spreadsheets, PDFs, scans, or other supported files.
What you see: the report and evidence enter the audit workflow.
Step 2
Recompute and trace
An independent AI auditor checks numbers and assertions against the original source documents.
What you see: source references, checks, and exceptions.
Step 3
Review the verdict
Receive a pass/fail result with supporting evidence and fixes where the system can resolve an issue.
What you see: a report you can review, explain, and stand behind.
Features, Grouped for FP&A Work
Core workflow features
- Independent AI auditor separate from the original agent
- Recomputation of numbers and assertions
- Source tracing to files, rows, and fields
- Pass/fail verdicts with supporting evidence
- Correction of issues where possible
Reliability & control
- Evidence trail for review and reproducibility
- Checks before delivery to stakeholders
- Reusable workflows that learn audit rules over time
- Enterprise-grade privacy and security positioning
- Reduced dependence on manual quality control
Integrations & export
- Support for 150+ file types
- Spreadsheets, PDFs, DOCX, scans, and complex documents
- CAD, G-code, InDesign, and BOM support
- White-label and brandable stakeholder-ready outputs
- Outputs designed for high-volume enterprise workflows
FP&A Forecast and Budget Audit Example
The supplied audit example tests a common distinction: a forecast updates expectations, while the adopted budget remains the original target and control baseline. Philadelphia FY2023 spending data makes the difference concrete.
Spending views
| View | Total spend | Meaning |
|---|---|---|
| Adopted Budget | $12.41B | Original contract, legal limit, and target |
| Estimated Budget | $6.06B | Formal update based on forecasts |
| Actual Spend | $5.92B | Year-end realized spending |
Relative scale of spending views
Adopted Budget$12.41B
Estimated Budget$6.06B
Actual Spend$5.92B
Actual spending was approximately 47% of the adopted budget.
Key variances from the audit example
- Estimated and actual spending fell by more than $6 billion from the adopted budget.
- Mental Health & Substance Use Services showed a 98% drop from adopted to actual.
- Commercial Corridors showed a 95% drop from adopted to actual.
- Police spending was 2.4% above the adopted budget.
- Trash & Sanitation spending was 2.1% above the adopted budget.
The CMA perspective distinguishes strategic planning, budgeting, forecasting, and variance analysis. In real-world FP&A practice, a forecast may not overwrite the original budget document, but it can change behavior through hiring freezes, transfers, capital reallocations, and other resource decisions. This is why forecast and budget auditing needs to examine both the arithmetic and the decisions connected to it.
Forecasting Does Not Technically Rewrite the Budget
Formal revisions
Forecasts can trigger transfers from areas forecasting surpluses to departments facing deficits. The total budget may remain unchanged while departmental budgets change.
Flexible budgets
Budgeted amounts can scale mathematically with volume metrics, such as units produced or citizen encounters.
Rolling forecasts
Progressive FP&A teams continuously forecast 12 months forward. By the second quarter, the annual budget may become more of a reference artifact when the rolling forecast drives allocation.
Verdict: technically, a forecast does not change the budget. Practically, forecasts change decisions by triggering hiring freezes, budget transfers, and capital reallocations.
Proof From Users and Published Claims
Powering workflows for 100,000+ clients worldwide.
Company cites 3× fewer hallucinations in public evaluations.
Company reports 94.4% accuracy on a published HuggingFace leaderboard.
Company reports 30% more accuracy than the listed second-place alternative in its leaderboard comparison.
“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.”
“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.”
Comparison: Energent Audit vs Other Review Approaches
| Dimension | Energent Audit | Original AI output | Human-only review |
|---|---|---|---|
| Independence | Separate auditor agent | The same system produced the work | Independent human reviewer |
| Number checking | Recomputes numbers | No independent check described | Performed manually |
| Source trace | File, row, and field evidence | May require separate checking | Depends on reviewer process |
| Verdict | Pass/fail with supporting evidence | Deliverable without stated audit verdict | Reviewer conclusion |
| Repeatability | Reusable workflows and audit rules | Depends on the original prompt and process | Depends on documented procedures |
The comparison describes the supplied workflow distinctions; it does not make a claim about every alternative product or review process.
Credentials & Key Stats
100k+
Clients worldwide
150+
File types supported
94.4%
Published leaderboard accuracy claim
#1
Cited placement on a HuggingFace leaderboard
Stats and performance statements are company-provided claims or descriptions from the supplied information.
See Energent Audit in Context
The supplied video explains how an independent agent retraces figures to their sources, verifies them, and presents a report that can be reviewed.
FAQs
AI audit for FP&A reports is the independent checking of financial reports, forecasts, budgets, numbers, and assertions created by AI or automation. Energent Audit uses a second agent that is separate from the agent that performed the original work. It recomputes numbers, traces figures to source files, rows, and fields, and checks the evidence supporting the result. It can issue a pass/fail verdict and attach supporting evidence. The goal is to let a reviewer focus on exceptions instead of treating the entire report as an unverified black box.
Yes, the supplied product information explicitly includes “Audit another AI’s work” as a shipped sample task. The auditor is described as independent from the AI that performed the work. That means the audit is not limited to Energent’s own outputs. An FP&A team can use the concept when multiple AI tools or automation systems contribute to a deliverable. The audit still depends on providing the relevant deliverable and source material for checking.
Energent states that the platform supports more than 150 file types. The supplied examples include spreadsheets, PDFs, DOCX files, scans, CAD, G-code, InDesign files, and bills of materials. This broad support is relevant when FP&A evidence is distributed across spreadsheets, documents, reports, and scans. The exact handling of a specific file should be confirmed in the product experience. The important audit requirement is that the source material used to support a figure is available for tracing.
Technically, the supplied audit conclusion says that a forecast does not change the adopted budget. The adopted budget remains the baseline for variance analysis and can remain the legal appropriation or agreed target. Practically, a forecast can change decisions through transfers, hiring freezes, capital reallocations, and other resource actions. Flexible budgets and formal revisions can also change budgeted amounts or departmental allocations under defined processes. In short, the forecast updates expectations, while those expectations can indirectly revise how resources are managed.
Energent describes a traceable chain from a number to the source file, field, and reference used to check it. The system recomputes numbers rather than only repeating the original answer. It also attaches supporting evidence to the pass/fail result. This gives a reviewer a path to investigate a flagged value or assertion. The supplied FP&A buyer message is that the result is complete, cited, and reproducible rather than opaque.
Specific pricing for AI Audit for FP&A Reports was not provided in the supplied information. The available product entry point is the Energent app, and a demo option is available for teams that want to discuss their workflow. Pricing may depend on the files, volume, workflows, and enterprise requirements involved. The page therefore does not state a price or invent a free-trial condition. A prospective buyer can use the product entry point or book a demo to obtain current details.
Catch AI Hallucinations Before They Cost You
Give FP&A reviewers a traceable pass/fail audit instead of another unsupported answer.