The group operated across multiple countries with a separate ERP in each.
Some were mainstream systems, some were non-standard platforms with no supported path into a common reporting layer. That left one version of the numbers per country and no reliable version for the group. Consolidation ran on spreadsheets and manual account mapping, rebuilt from scratch every reporting cycle. Any question from outside the company restarted that work. A sale process put a clock on it. Because country totals never tied to group, the quality of earnings firm kept re-pulling revenue by entity rather than accepting it, and information requests took most of a week to answer. What was missing was a single consolidated view that held up under questioning without being rebuilt each time someone asked.
Scaylor connected each of Exchangers Industries' country ERPs in place, with no migration, and used AI agents to propose cross-system account matches that the finance team approved or corrected. A tribal knowledge graph captured why accounts were set up as they were, so one reconciled set of group figures stays current and answerable through Gemini-driven queries.
Diligence requests answered the same day instead of the following week.
Reduction in finance team hours spent on manual data reconciliation.
Eliminated repeat data pulls by the quality of earnings firm.
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