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Financial Services

A Global Bank Cut Decision Time by 40% After Unifying Its Data on an Agentic AI Layer.

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OVERVIEW

From Data Silos to a Unified AI Intelligence Layer

A global-scale African bank specializing in digital banking, financial inclusion, and enterprise-grade financial solutions was generating significant data every day, but none of it was connected. Critical information sat fragmented across Databricks environments, core banking systems, and internal applications with no unified layer to surface it.

Without a connected data layer, business teams relied on manual aggregation. Insights that should take minutes took days. The bank needed its data AI-ready, and one layer to connect everything.

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CHALLENGES

Fragmented Data Across Every System That Mattered

The bank's infrastructure had grown organically over years, resulting in fragmentation at every level; no single source of truth, and business teams consistently operating on incomplete information.

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Data was distributed across multiple systems with no mechanism to surface it in real time.

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Business teams could not get unified insights due to fragmentation across Databricks, core banking, and internal applications.

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Complex datasets required manual cross-system lookups with no intelligence layer to interpret them.

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Existing infrastructure was not AI-ready - data existed but could not be reasoned over or acted on.