Accounting Logic, Applied Consistently at Scale
Matching rules are defined once and applied every period. Support one-to-one, one-to-many, and many-to-many scenarios. Execution stays consistent across entities and volumes.
High-volume transaction matching is prepared continuously using a next-generation matching engine, so alignment happens before close pressure begins.

Matching rules are defined once and applied every period. Support one-to-one, one-to-many, and many-to-many scenarios. Execution stays consistent across entities and volumes.
AI preparers go beyond rigid rules to resolve real-world accounting data.
• Fuzzy matching handles inconsistent descriptions and references.
• Pattern recognition identifies related transactions across sources.
• Partial matches, timing differences, and data irregularities are supported.
• 35% reduction in manual investigation.
Only what requires professional review rises to the surface.
• Policy-driven thresholds automatically clear immaterial activity.
• Unmatched and partial matches clearly flagged.
• Each exception includes context, source data, and rationale.
• Review effort is focused and not fragmented.
Transaction matching operates as part of close execution, not as a standalone activity.
• Matching outcomes flow directly into account reconciliations.
• Aligned transactions reduce downstream variance analysis.
• Parallel investigation across tools and spreadsheets eliminated.
• Close preparation accelerates as matching completes.
Every match remains explainable and audit-ready.
• Clear lineage from source transaction to matched outcome.
• Reviewer actions, comments, and approvals preserved.
• Supporting evidence retained alongside results.
• Audit readiness is built in and not reconstructed later.
Free your team from manual matching, without losing control.
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