Case Study: Brex improves transaction enrichment and reconciliation with Ntropy AI

Brex boosts transaction accuracy 15% with Ntropy

Brex, a business bank focused on improving financial operations for small and medium-sized businesses (SMBs), sought to enhance its automation by moving beyond basic copilot features. They needed to replace their patchwork of legacy ML models and vendors with a more reliable and unified approach for tasks like transaction classification and enrichment, which were costly and difficult to maintain internally. To solve this, they turned to the Ntropy AI platform and its transaction enrichment service.

By implementing Ntropy's solution, Brex saw a significant 10-15% improvement in accuracy for key metrics like label and merchant identification on a set of difficult transactions. The solution from Ntropy provided better results with less operational overhead, leading to faster book-closing and reconciliation for their customers. This allowed Brex to avoid the complex in-house development of LLM orchestration and infrastructure, saving their finance teams considerable time.

Brex