A financial services firm with an established graph data ecosystem faced scalability challenges as reliance on graph-based solutions grew across business units. Increasing data volumes and concurrent usage exposed system limitations, leading to cluster instability that disrupted downstream pipelines and delayed critical analytical and operational processes. The platform also lacked advanced reasoning capabilities and fine-grained access controls, restricting effective data governance and consistent application of business logic. Additionally, an inflexible upgrade path made it difficult to adapt the system, limiting the firm’s ability to scale securely and support expanding analytical needs across teams.

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