Straive

The client operated across more than 20 legal entities in over 30 markets using five to six different ERP systems, resulting in a highly fragmented data landscape. The distributed environment prevented centralized data management, consistent enterprise reporting, and effective Master Data Management (MDM), making it difficult to establish a unified view of business data across the organization.

Straive designed and implemented a scalable cloud-based enterprise data platform built on a modern Azure-focused data architecture. The solution established a unified lakehouse supporting both batch and real-time data ingestion, integrated Master Data Management (MDM) and governance frameworks to synchronize data across multiple ERP environments, and developed hybrid connectivity layers to ingest and process data from legacy on-premises systems into a centralized cloud platform. The platform enabled centralized governance while allowing decentralized access across regional business units.

The client experienced lengthy commercial customer onboarding cycles because legal and financial documents were processed manually. The manual approach resulted in long turnaround times, inconsistent customer data quality, and delayed onboarding of new commercial accounts.

Straive implemented an AI-driven data ingestion and enrichment framework to modernize the client's information lifecycle. The solution automated extraction and classification of complex legal and financial documents, integrated internal and external data sources into existing enterprise data pipelines, and created enriched real-time customer profiles to support faster onboarding and improved data quality. Embedded AI models were incorporated during the ingestion process to strengthen fraud detection.