Detect cash flow-to-earnings drift before it costs you, with independently recomputed figures, source-level evidence, and a clear pass/fail verdict.
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Cash flow to net income drift analysis compares operating cash flow with reported net income to identify where earnings and cash generation begin to move apart. Energent Audit independently recomputes the ratio, the dollar variance, and related working-capital signals from the original source documents. It then traces every figure to its source file, row, and field, fixes errors where possible, and produces a reviewable pass/fail result. This gives finance, accounting, diligence, and analysis teams a way to review AI-generated work without becoming the permanent quality-control layer.
For teams building a broader financial analysis workflow, the same evidence-first approach can support recurring analysis across spreadsheets, PDFs, scans, presentations, and other complex files.
The following figures come from the provided Financial Due Diligence Red Flags Dashboard, published June 29, 2026. They illustrate how an audit can distinguish a ratio near parity from a wider multi-year drift pattern.
Operating cash flow generally remained above earnings in the observed years, but FY2025 became the first reported point below the 1.0× parity level. Operating cash flow was unavailable for FY2014–FY2016, which are retained as intentional gaps rather than interpolated values.
| FY | Growth Gap | Allowance Ratio | Accrued Swing | OCF / NI | OCF − NI | Watch Score |
|---|---|---|---|---|---|---|
| 2012 | +59.0pp | 0.90% | +213.5% | 1.22× | $9.1B | 70/100 |
| 2018 | +13.9pp | 0.00% | n/a | 1.30× | $17.9B | 66/100 |
| 2020 | −35.2pp | 0.00% | n/a | 1.41× | $23.3B | 65/100 |
| 2022 | −0.5pp | 0.00% | n/a | 1.22× | $22.3B | 64/100 |
| 2021 | +29.8pp | 0.00% | n/a | 1.10× | $9.4B | 63/100 |
| 2024 | +11.2pp | 0.00% | +3.4% | 1.26× | $24.5B | 55/100 |
| 2019 | +0.9pp | 0.00% | n/a | 1.26× | $14.1B | 53/100 |
| 2023 | +7.5pp | 0.00% | +94.3% | 1.14× | $13.5B | 53/100 |
A reviewable report connects the verdict to the analysis and its supporting evidence.
The audit is designed for the reports that matter most: it retraces figures to their source, verifies how they were built, and shows the reviewer what can be supported.
The same evidence trail can complement financial due diligence and recurring review processes. Instead of treating an AI answer as final, the independent auditor checks the underlying work before delivery.
Connect cash flow, net income, ratios, and variances to the exact source file, row, and field.
Recalculate the cash flow-to-earnings relationship rather than accepting the first AI-generated result.
Identify unsupported figures, calculation errors, and watched financial-risk signals before delivery.
Receive complete, cited, reproducible analysis with a pass/fail verdict and supporting evidence.
Save repeating jobs as workflows so corrections can become persistent audit rules for future work.
Review spreadsheets, PDFs, Word documents, presentations, scans, CAD, G-code, and other supported formats.
Provide the analysis and its original reference files for independent review.
What you see: your source-grounded job begins.A separate agent checks every calculation and follows each figure back to its source.
What you see: evidence, references, and flagged differences.Receive fixes where possible, plus a clear pass/fail result with a reproducible audit trail.
What you see: a report you can stand behind.The provided dashboard includes an earnings-to-cash conversion view, an EBITDA-to-free-cash-flow bridge, CAPEX versus D&A analysis, and margin decomposition.
This type of bridge can be paired with cash flow and EBITDA bridge analysis when the review requires more than a single ratio.
The FY2015–FY2025 dashboard compares the profit engine, liquidity, debt, capital returns, and annual financial statement trends.
Teams can use this evidence in broader equity research analysis without losing the source trail.
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| Review dimension | Energent.ai | Original AI output | Manual review |
|---|---|---|---|
| Independent recomputation | Yes, by a separate auditor | Not stated | Depends on reviewer |
| Source-level traceability | File, row, and field | Not guaranteed | Reviewer-dependent |
| Pass/fail evidence trail | Included | Not guaranteed | May be assembled manually |
| Reusable audit rules | Workflows can be saved and rerun | Not specified | Often repeated manually |
| Complex file support | 150+ file types stated | Varies by system | Varies by tools and expertise |
The comparison uses only capabilities and review characteristics provided for Energent.ai; generic alternatives are described neutrally rather than as named competitors.
clients worldwide
published leaderboard accuracy
supported file types
fewer hallucinations claim
Recognized across the company’s cited ecosystem
It is an independent review of the relationship between operating cash flow and reported net income. The analysis recomputes the ratio and the dollar difference from source materials rather than accepting an AI-generated conclusion as final. It can also examine related signals such as receivables growth, allowance coverage, and accrued-liability swings. Energent Audit presents the result as a cited, reproducible pass/fail analysis with an evidence trail.
It is intended for analysts, finance and accounting teams, operations and procurement groups, research teams, and enterprise users handling high-stakes analysis. It is particularly relevant when AI or automation has already produced a spreadsheet, report, dashboard, or diligence deliverable. Users can focus their review on flagged rows instead of checking every calculation manually. The provided use case shows how the approach can support financial due diligence and recurring cash-conversion work.
An independent agent first reviews the completed analysis. It recomputes cash flow, net income, ratios, and variance figures, then traces each number to the exact source file, row, and field. It checks the calculations against the original reference and fixes errors where possible. Finally, it issues a pass/fail verdict with supporting evidence so the result can be reviewed and reproduced.
Energent.ai states that it supports more than 150 file types, including financial files, spreadsheets, PDFs, Word documents, presentations, scanned images, CAD, G-code, InDesign files, and BOMs. The provided output examples include Excel workbooks with live formulas and audit-trail tabs, Word documents, PowerPoint decks, annotated PDFs, filled tax forms, ZIP packages, and HTML dashboards. Support is designed for complex and high-volume enterprise workflows. The exact files used in a particular job determine the resulting output format and evidence available.
Yes. The provided use case explicitly describes the ability to audit another AI’s work, not only work produced by Energent.ai. The auditor is separate from the system that performed the original task, so it has no stake in the first answer. It independently recomputes and traces the result before delivery. This separation is intended to catch unsupported numbers and hallucination errors that may otherwise pass through a normal AI workflow.
Specific pricing details are not provided in the supplied use-case information. The available product entry point is the Energent.ai application, and a demo can be requested through the company website. Teams evaluating the workflow can review the stated file support, audit process, evidence trail, and recurring workflow capabilities. For current plan availability and onboarding details, use the company’s pricing or demo pages rather than relying on an unstated estimate.
Run an independent cash flow-to-net-income audit with evidence your team can review.