Upload your legacy chart and receive proposed mappings to the standardized structure. The system spots patterns across names, numbers, and categories, suggesting placements that mimic real-world usage. You approve in batches, override where needed, and save reusable rules for mergers or future entities. This learning loop preserves institutional knowledge while eliminating inconsistent ad hoc mappings that cause reconciliation drift, making your first close on the new platform clean, predictable, and pleasantly uneventful.
Before data lands, rules scan for unbalanced journals, missing tax codes, unsupported currencies, and inactive employees. Error queues prioritize the most impactful fixes, with inline explanations and one-click corrections. Rather than discovering problems after posting, you resolve them at the gate. This approach prevents cascading inaccuracies, reduces rework, and maintains credibility with leaders who need dependable numbers the first time, not after days of patching spreadsheets and chasing down conflicting reports.