Structured Ingestion
Native parsing of GLs, trial balances, and operational data across formats and ERPs — into a single canonical model.
By reducing repetitive spreadsheet-driven workflows and manual analytical assembly, DDengine enables more rapid progression from data ingestion to senior-level review and transaction insight.
Standardized templates and governed taxonomies move data from raw room to defensible output — designed for repeatability across mandates.
Reduced cycle time through automated reconciliation and confidence-scored review. Insight delivered at the cadence diligence requires.
Every figure traces back to source. Auditable, reviewable, and built to withstand scrutiny from IC, lender, and seller alike.
An operational layer for diligence — purpose-built for repeatable, auditable M&A workstreams. Structured ingestion, reconciliation frameworks, governed classification, benchmarking, confidence scoring, management-question generation, and review workflows operate as one governed system rather than disconnected analysts and spreadsheets.
Native parsing of GLs, trial balances, and operational data across formats and ERPs — into a single canonical model.
Governed tie-outs between management figures, audited statements, and supporting schedules — with reviewable exception flagging.
Centrally maintained taxonomies for revenue, cost, and adjustment categorization — applied consistently across mandates and reviewable at every step.
Comparable cohort analysis across margin, working capital, and unit economics — drawn from a curated reference set.
Statistical and rule-based assessment of figure reliability across the deal model — analysts review what matters first.
Targeted management-question generation paired with multi-stage analyst, manager, and partner review workflows — every step audited and reviewable.
DDengine is offered to a limited cohort of private equity sponsors and corporate development teams. Briefings are by request.