A regional retail bank had 12 AI pilots stuck in place for over a year, and the root cause wasn’t the models — it was that the data those models needed lived in nine disconnected systems with no consistent access layer.
Building a Hybrid Data Platform to Unblock 12 Stalled AI Pilots
Service Provided
Capabilities Utilized
Data Architecture, Hybrid Infrastructure, Data Governance
Client challenge
Customer, transaction, and risk data were scattered across on-premises core banking systems, a handful of cloud data warehouses from prior acquisitions, and departmental spreadsheets. Every AI team that tried to build a pilot spent most of its time just tracking down and cleaning data, and each team was solving the same data-access problem independently.
Our solution
We designed a hybrid data platform that left sensitive core banking data on-premises — satisfying the bank’s existing regulatory and latency constraints — while standing up a governed cloud layer for everything that could safely move, with a unified access API sitting in front of both. AI teams query one interface regardless of where the underlying data physically lives.
We paired the platform build with a data governance layer defining ownership, quality standards, and access controls per data domain, so the platform wouldn’t just centralize access but also centralize accountability for data quality.
Results
Nine of the twelve stalled pilots resumed active development within the first quarter after platform launch, and five reached production within eight months — more than the bank had shipped in the prior two years combined. Average time from pilot kickoff to a working prototype dropped from an estimated 14 weeks to 5 weeks, driven almost entirely by the elimination of manual data-gathering work.
Additional Case Studies
Launching a Usage-Based Pricing Model for an AI Developer Platform
An AI developer platform’s flat-tier pricing was leaving money on the table with its largest customers
Establishing an Enterprise AI PMO to Track ROI Across 30 Initiatives
A global enterprise had 30 active AI initiatives across its business units but no consistent way
Building the Product Operating Model for an Agentic SaaS Vendor
A vertical SaaS vendor had shipped an early agentic feature that could autonomously complete customer workflows,
