Energent Audit for investment workflows

Financial Modeling for Private Equity Without Manual AI Quality Control

Recompute model outputs, trace assumptions to source files, and catch unsupported numbers before an investment deliverable reaches review.

Ask Energent to audit a model, spreadsheet, or report

Attach files in the product experience after selecting Run Audit.

94.4%
Published leaderboard accuracy claim
150+
Supported file types
Fewer hallucinations in public evaluations
100K+
Clients worldwide

Trusted by 100k+ companies across the globe.

Amazon
AWS
UC Berkeley
Experian
GE
PwC
Stanford
Amazon
AWS
UC Berkeley
Experian
GE
PwC
Stanford

What Is Financial Modeling for Private Equity?

Financial modeling for private equity is the process of turning operating, financing, market, and company data into a structured view of an investment’s performance, risk, and potential outcomes. Energent Audit adds an independent verification layer to that workflow: a separate AI agent recomputes figures, traces them to the exact source file, row, and field, checks assertions against references, and returns a pass or fail verdict with evidence. It is designed for analysts, finance teams, operations groups, and other professionals who need a model or investment deliverable they can defend in review.

For teams evaluating private equity due diligence, this means shifting from verifying every row manually to reviewing the exceptions that the audit surfaces. The workflow can also support AI financial modeling when generated analysis must be checked before distribution.

A Live Audit, Start to Verdict

The following assets show the type of analytical and audit-ready output that can be reviewed with Energent. Images are displayed in full without cropping.

Energent Audit report screenshot showing a Project Cash Flow Dashboard

Project Cash Flow Dashboard

An audit report can make coverage, break-even occupancy, cash-flow pressure, and scenario assumptions visible in one reviewable output.

From Number to Evidence

The demonstration explains how an independent agent retraces figures to their sources, verifies the result, and produces a report that can be stood behind.

Financial due diligence red flags dashboard

Financial Due Diligence View

A red-flag dashboard format helps organize KPI cards, notes, and visual findings for a finance review.

Technical drawing gap analysis dashboard

Structured Analytical Output

Energent supports complex documents and analytical deliverables, including dashboards that present findings alongside source-grounded metrics.

Private Equity Modeling Evidence in the Supplied Data

These tables use figures from the supplied dashboards. They are examples of the kinds of coverage, scenario, operating leverage, and macro diagnostics that an investment team may need to inspect; they are not presented as a valuation of a specific private equity target.

Scenario scorecard

10-year rental property cash-flow stress test supplied in the audit material.

ScenarioMin DSCRYears below 1.0x10Y cash flow
Baseline1.02xNone€28.8K
Rate shock (+200 bps)0.87x8-€17.7K
Stagflation0.79x9-€24.4K

The same supplied dashboard reports a €620.0K Year 1 entry value and a peak break-even occupancy of 73.6% under stagflation.

Operating leverage checkpoint

Software and payments operating leverage dashboard, last five reported years.

YearRevenueGross marginOperating income
2021$282.9M22.0%-$53.9M
2022$355.8M25.1%-$58.0M
2023$415.8M23.6%-$59.7M
2024$350.0M41.8%-$79.1M
2025$455.5M43.5%-$68.8M

The supplied interpretation notes that gross margin improved in 2024 and 2025 while operating expenses remained above gross profit.

Macro and model-risk diagnostics

The supplied macro-financial diagnostics show why investment models need scenario and timing checks rather than relying only on an attractive in-sample fit.

98.1%
Spurious regression R² in levels
19.0%
Corrected R² in differences
80.0%
Naive lookahead R²
18.6%
Realistic lagged-data R²

These supplied figures illustrate the importance of checking assumptions, data timing, and model reproducibility when an output will inform an investment decision.

What You Get

Trace every number to its source

Review the source file, row, field, and reference behind a figure instead of accepting an unexplained result.

Recompute the important calculations

Have the independent auditor recalculate numbers and check assertions before a deliverable reaches stakeholders.

Focus review on what is flagged

Move from verifying every row to investigating the exceptions surfaced by the audit.

Produce a pass/fail verdict

Receive a clear decision with evidence attached, including failures that can be corrected before delivery.

Turn recurring checks into workflows

Reusable workflows learn audit rules over time so corrections can become persistent checks.

Work across complex files

Use support for 150+ file types, including spreadsheets, PDFs, scans, CAD, G-code, and complex documents.

How It Works

Step 1

Submit the deliverable

Provide the spreadsheet, PDF, scan, CAD file, or other source material and describe the audit you need.

What you see: a defined audit task and the files it will inspect.

Step 2

Let the auditor recompute

A separate agent retraces figures, checks assertions against the original sources, and fixes what it can.

What you see: calculations, references, and flagged discrepancies.

Step 3

Review the verdict

Use the evidence trail and pass/fail result to approve the output or resolve the issues before delivery.

What you see: a reviewable report you can cite in a meeting.

Features, Grouped

Core workflow features

  • Independent AI auditor separate from the working agent
  • Natural-language prompts for high-stakes analysis
  • Audit another AI’s work, not only Energent output
  • Reusable workflows that learn audit rules
  • White-label and brandable stakeholder-ready outputs

Reliability & control

  • Recomputation of numbers and assertions
  • Source, row, and field-level traceability
  • Clear pass/fail verdicts
  • Evidence attached to failures
  • Enterprise-grade privacy and security emphasis

Integrations & export

  • Support for 150+ file types
  • Spreadsheets, PDFs, DOCX, scans, and complex documents
  • CAD, G-code, InDesign, and BOM support
  • Reviewable analytical dashboards and reports
  • Brandable outputs for stakeholders

Proof: Results and Social Proof

  • Energent reports 94.4% accuracy on a published HuggingFace leaderboard and a number-one placement on the cited leaderboard.
  • The company cites 3× fewer hallucinations in public evaluations and says its result was 30% more accurate than the listed second-place alternative in that comparison.
  • Energent supports 150+ file types and is described as powering workflows for more than 100,000 clients worldwide.
  • The supplied audit examples include financial due diligence, cash-flow stress testing, operating leverage, and macro-financial model diagnostics.

“I had spreadsheets with more than 45K items and Energent AI was the only tool that was able to sort through everything.”

Roberto C., Data Operations Specialist, Fortune 500 Logistics

“Not only did I ultimately choose Energent.ai, but you are the absolute best BY FAR.”

Alyse H., Digital Collection Curator, Fortune 500 Retail & E-commerce

“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.”

Kay P., Power Query Analyst, Fortune 50 Financial Services

“Energent.ai is a great platform... the interactive outputs add real value to my work.”

Amjad M., Telecommunications Engineer, Fortune 500 Telecommunications

Comparison: Why Energent vs Alternatives

Decision dimension Energent Audit Generic Alternative A: unaudited AI output Generic Alternative B: manual review
IndependenceSeparate AI auditor checks the workNo independent second agent is specifiedDepends on a human reviewer
Numerical verificationRecomputes numbers and assertionsOutput is not described as recomputedReviewer recalculates manually
Evidence trailTraces figures to source file, row, and fieldMay require separate investigationEvidence must be assembled by the reviewer
VerdictClear pass/fail result with evidence attachedNo stated pass/fail audit layerJudgment is recorded through the review process
RepeatabilityReusable workflows can learn audit rulesRules may need to be restatedConsistency depends on the reviewer
File coverage150+ file types, including CAD and scansCoverage varies by toolCoverage depends on available expertise and tools

The alternatives are generic workflow categories, not named competitor products. Rows reflect the capabilities and workflow distinctions supplied for Energent Audit.

Credentials & Key Stats

94.4%

Accuracy on a published HuggingFace leaderboard, company claim

150+

Supported file types

Fewer hallucinations in public evaluations, company claim

100K+

Clients worldwide, company-reported

FAQs

Yes, it is relevant when a private equity team needs to verify model outputs, source data, assumptions, or analytical deliverables. Energent Audit is an independent AI auditor that checks work produced by another AI agent or workflow. It recomputes numbers and traces them to the exact source file, row, and field where available. It can therefore support review of cash-flow scenarios, debt coverage, operating leverage, and other supplied analytical outputs. It does not replace investment judgment or the team’s approval process.

Energent uses a second agent that is separate from the agent that performed the original work. That auditor recomputes numbers, checks assertions, and retraces figures to their source material. It can fix issues it identifies and attaches evidence to failures. This creates a reviewable chain rather than leaving the original output as the only reference. The company cites 3× fewer hallucinations in public evaluations, which is a company-reported claim.

Energent states that it supports more than 150 file types. The supplied description includes spreadsheets, PDFs, DOCX files, scans, CAD, G-code, InDesign files, and bills of materials. This breadth is intended for workflows that combine structured and unstructured source material. The exact handling of a particular file should be confirmed in the product experience. File support does not mean that every file will contain sufficient information for a particular audit.

Yes, the supplied feature description explicitly says that Energent Audit can audit another AI’s work. One shipped sample task is described as “Audit another AI’s work.” The auditor is not limited to checking only Energent’s own output. It evaluates deliverables against source documents and references. Teams should still define the scope of the requested audit clearly so the relevant calculations and assertions are checked.

The feature is designed to produce a clear pass/fail verdict with an evidence trail. It identifies the source file, field, and reference behind a number when tracing is available. That structure is intended to make findings reviewable and reproducible rather than presenting a black-box answer. The supplied buyer language describes the result as complete, cited, and defensible in a review meeting. Final suitability depends on the team’s own governance, documentation, and investment-committee requirements.

The supplied information does not provide specific pricing amounts or onboarding timelines. Energent provides a product entry point and a book-a-demo option for teams that want to explore the workflow. A demo can clarify the appropriate file types, audit scope, and output format for a private equity use case. Pricing may depend on the relevant product or workflow arrangement, but no unsupported figure is provided here. Teams should contact Energent directly for current commercial details.

Catch unsupported numbers before they reach investment review.

Run a source-grounded audit on your next financial model or analytical deliverable.