Energent Audit independently recomputes AI-generated reconciliations, traces every figure to its source, and returns a reviewable pass/fail verdict before the work reaches you.
AI reconciliation verification software checks whether an AI-generated reconciliation, report, spreadsheet, or analysis agrees with the original source documents. Energent Audit acts as a separate auditor: it recomputes numbers, follows each figure back to the exact source file, row, and field, identifies unsupported conclusions, fixes errors where possible, and attaches evidence to a pass/fail result. It is designed for finance, accounting, operations, procurement, engineering, research, and other teams that need defensible outputs without manually checking every row.
For teams evaluating AI output verification, the central distinction is independence. The auditor is separate from the agent that performed the original work, so review focuses on reproducibility and evidence rather than trusting the first answer.
The following examples show the kinds of reconciliation findings Energent Audit can surface in source-backed reports.
A Philadelphia FY2023 review compared an adopted budget of $12.41 billion, an estimated budget of $6.06 billion, and actual spend of $5.92 billion. The audit identified that actuals were approximately 47% of the adopted budget and highlighted category-level changes, including a 98% drop for Mental Health & Substance Use Services and a 2.4% increase for Police.
Explore financial reconciliationEnergent supports complex deliverables such as CAD, scans, G-code, BOMs, spreadsheets, and documents. Its audit approach can check source-data aggregations, workbook configuration, chart references, column ordering, and off-by-one indexing errors instead of limiting review to plain text.
Review technical AI auditsOne report found 11,801 sessions missing source and campaign tags, separating 6,075 legitimate organic-search sessions from 5,726 direct type-ins. It also verified that line-item sums aligned with total order prices, while identifying a rise in refunds from $3.2k to $7.8k and a likely supplier quality-control or inventory-batch issue.
See revenue verification workflowsA spend audit reconciled $1,284,500 of Q1 spend across 412 rows to vendor invoices. It corrected an 18% increase to 12.0% because the original comparison excluded Facilities from the Q4 subtotal, and it flagged an unsupported claim that Software had grown approximately 30% quarter over quarter.
Analyze vendor spendReview what is flagged instead of manually checking every row, whether the job contains eight rows or 500.
Surface reconciliation issues before delivery rather than discovering them a month or two later.
Follow a figure to its exact source file, field, row, and reference used during verification.
Use complete, cited, reproducible evidence in a review meeting or stakeholder discussion.
Receive corrections for issues the auditor can resolve, while unsupported or incorrect derived figures remain flagged.
Use the independent auditor to check work produced by another AI agent, not only Energent output.
Provide the AI-generated deliverable and its source material for independent review.
What you see: a review-ready audit begins.
The independent agent recomputes numbers and checks each figure against source evidence.
What you see: cited findings and detected discrepancies.
Get corrections where possible and a pass/fail result with supporting evidence attached.
What you see: a report you can stand behind.
Teams comparing enterprise AI audit software can also use Energent’s reusable workflows, which learn audit rules over time so recurring corrections can become persistent checks.
“I had spreadsheets with more than 45K items and Energent AI was the only tool that was able to sort through everything.”
| Capability | Energent Audit | Generic AI workflow | Manual review |
|---|---|---|---|
| Independent verification | Separate auditor agent | Not specified | Human reviewer |
| Number recomputation | Included in audit process | Not specified | Performed manually |
| Source tracing | File, row, and field evidence | Not specified | Depends on reviewer process |
| Pass/fail verdict | Attached to audit report | Not specified | Depends on review format |
| File coverage | 150+ file types stated | Not specified | Depends on available tools |
supported file types
published leaderboard accuracy
fewer hallucinations claimed
clients worldwide
Trusted by 100k+ companies across the globe.
AI reconciliation verification software independently checks whether AI-generated numbers and conclusions agree with their source documents. It recomputes figures, traces them to the exact file, row, and field, and identifies unsupported or incorrect claims. Energent Audit also produces a pass/fail verdict with evidence attached. This makes the output easier to review and defend. The concept is useful when an AI-generated reconciliation is too important to accept without verification.
Energent Audit is intended for analysts, finance and accounting teams, operations and procurement groups, engineering and CAD teams, research groups, and enterprise customers. It is especially relevant when teams produce reconciliations, spreadsheets, reports, or other deliverables with AI assistance. The platform is designed to reduce the amount of manual checking required before delivery. It can also audit work produced by an AI system other than Energent. The strongest fit is a workflow where traceable evidence and reproducibility matter.
The process starts with an independent AI agent reviewing the completed work. It recomputes numbers and traces each figure back to the exact source file, row, and field. It then checks the deliverable against source evidence and fixes errors where possible. The result includes a pass/fail verdict and supporting evidence. Audit examples also show checks for aggregations, chart references, column ordering, workbook configuration, and indexing errors.
The provided company information states that Energent supports more than 150 file types. Examples include CAD files, scans, G-code, InDesign files, bills of materials, PDFs, XLSX files, and DOCX files. The broader description also refers to spreadsheets, complex documents, and other enterprise deliverables. Exact handling can depend on the specific workflow and source materials. The stated file coverage is intended for high-volume, mixed-format work rather than only simple text documents.
Energent Audit is designed to detect unsupported numbers and assertions by checking them against original source documents. It recomputes figures, traces evidence, and flags findings that do not reconcile. The company cites 3× fewer hallucinations in public evaluations, which is a company claim rather than an independently established guarantee. An audit can identify problems, but teams should still apply appropriate judgment to important decisions. The evidence trail helps reviewers understand exactly why a finding passed or failed.
You can begin through the Energent app or request a product demonstration from Energent.ai. The provided information does not include specific pricing figures, so this page does not state a price. A demo can help teams discuss their documents, reconciliation workflow, and review requirements. The platform also provides reusable workflows so recurring audit rules can be retained over time. For current plan and onboarding details, use the official product and demo links above.
Verify AI-generated work with an independent audit, source-traced evidence, and a clear verdict.