Automated financial diagnostics that transforms balance sheets into structured, investor-grade data. Phase 1 is live now.
AI-driven line-item analysis that identifies inconsistencies, misclassifications, and structural issues across current and prior period statements.
Automated mapping of financial statement categories to IRS-standard classifications — ensuring clean chart-of-accounts alignment for any transaction or audit review.
Cross-document validation that detects discrepancies between income statements and balance sheets — one of the most common pre-transaction data failure points.
Automated flagging of mathematical errors, category mismatches, unusual period-over-period variances, and structural anomalies in financial records.
Validates EBITDA calculations, identifies add-back items, normalizes owner distributions, and structures output for investor or lender presentation.
Produces structured financial data packages suitable for M&A due diligence, SBA/bank lending, private equity review, or strategic buyer presentations.
| Phase | Status | Scope |
|---|---|---|
| Phase 1 — Core Diagnostics | Live | Balance sheet review, EBITDA validation, basic discrepancy detection |
| Phase 2 — Enterprise Platform | In Development | Multi-entity support, API integrations, white-label delivery, automated reporting |