Flag anomalies before
the audit begins.

AuditPulsar scans every journal entry in your client's general ledger, identifies irregular postings, and surfaces discrepancies your team would otherwise find 40 hours in.

97.3%
Anomaly detection accuracy on held-out test sets
43%
Reduction in manual journal-entry review hours
2.4s
Average ledger scan time per 10,000 transactions
SOC 2
Type II certified. Client data never leaves your tenant.

Built for the audit room, not the pitch deck

Every feature was tested against real client ledgers before it shipped.

Journal Entry Screening

Automatically reviews every debit-credit pair against client-specific thresholds. Flags round-number postings, after-hours entries, and entries that bypass the normal approval chain.

Ledger Reconciliation Engine

Traces trial balance discrepancies to their source account in seconds. Cross-references subledger totals with general ledger aggregates across GAAP and IFRS reporting frameworks.

Anomaly Scoring

Each flagged transaction receives a risk score (0–100) based on statistical deviation, account history, and peer-group benchmarks. Reviewers triage by score, not intuition.

ERP Integrations

Direct connectors for SAP S/4HANA, Oracle NetSuite, and QuickBooks Enterprise. CSV and Excel import supported for any other system. No manual data transformation required.

Audit-Ready Reports

Exports workpapers in PCAOB-compatible format. Each anomaly finding includes the account code, transaction date, preparer ID, and supporting evidence trail.

Audit Trail & Controls

Every action — scan initiation, finding acknowledgment, workpaper sign-off — is logged with timestamp and user identity. Meets requirements for AS 2201 internal controls review.

From ledger import to signed workpaper

Three steps. No consulting engagement required to get started.

01

Connect Your Data Source

Authenticate against the client's ERP via OAuth 2.0 or upload a trial balance export. AuditPulsar ingests general ledger data in SAP BAPI, Oracle REST, or flat-file CSV format.

02

Run the Anomaly Scan

The detection engine applies statistical sampling, Benford's Law analysis, and supervised ML models trained on 14.7M historical journal entries. Scan completes in under 90 seconds for most engagements.

03

Review Findings & Export

Auditors work through a prioritized findings queue. Each item links back to source transactions. Export to PDF workpaper or directly to your document management system.

See how the detection engine works

The product page covers the ML architecture, supported ERP integrations, and how risk scores are calculated.

Explore the Platform

What audit teams report after using AuditPulsar

Mid-Market Assurance Firm

"We started using AuditPulsar on a manufacturing client with 120,000 journal entries per quarter. The platform surfaced 14 high-risk items in the first scan — three of which became reportable findings. We cut field time by 31%."

Regional CPA Practice

"Our staff no longer exports the trial balance to Excel and runs manual pivot tables. The SAP connector pulls data directly, and the ledger reconciliation report is something we can hand to the client on day one."

Big-4 Internal Audit Team

"We piloted on two engagements before committing. The anomaly scores tracked well against our senior reviewers' judgment. The PCAOB workpaper export alone justified the subscription."