What challenges did Pave Bank face before AI implementation?

Developing a new digital banking platform that is innovative, scalable, and capable of incorporating generative AI. Building an infrastructure that supports AI-driven product development and simplifies data analytics and container operations.

What was the impact of the AI solution?

Accelerated product development and innovation through integrated generative AI capabilities. Reduced manual data science scripting through automated analytics with BigQuery. Improved operational efficiency and achieved cost savings. Positioned Pave Bank as a technology-driven financial services innovator.

Source

GCPProductionEvidence: Medium55/100

Pave Bank Builds Digital Bank with Integrated Generative AI on Google Cloud

Use case typeDigital bankingUpdated Jun 13, 2026

Pave Bank, a startup operating in Singapore and Georgia, developed a modern digital banking platform from the ground up leveraging Google Cloud technologies. The company integrated generative AI capabilities deeply into its core banking infrastructure using Google Cloud Vertex AI and Model Garden to accelerate product development and operational innovation. They utilized Google Cloud data services including BigQuery for analytics automation and Cloud SQL, Dataflow, Pub/Sub, Cloud Run, Kubernetes for scalable containerized infrastructure. The integration enabled Pave Bank's engineering teams to make AI-driven decisions and accelerated innovation with cost and efficiency improvements. Pave Bank is dedicated to reimagining banking with a technology-first approach combining finance products with AI-driven operations.

Organization: Pave Bank
Industry: Finance
Location: Singapore
Published: January 2023

Reported outcomes

Strategic outcomes

New product / capabilityBuilt a digital banking platform with generative AISpeed & agilityAccelerated product development and innovationBetter decisions & insightEnabled AI-driven predictive decision-makingCost efficiencyImproved operational efficiency and cost savings

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Pave Bank
Provider: GCP
Maturity: Production
Linked source: Google Cloud Customer Stories

The company integrated generative AI capabilities deeply into its core banking infrastructure using Google Cloud Vertex AI and Model Garden to accelerate product development and operational innovation

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 2 of 2

1Digital Banking
2Generative AI Integration

Developing a new digital banking platform that is innovative, scalable, and capable of incorporating generative AI.
Building an infrastructure that supports AI-driven product development and simplifies data analytics and container operations.

Built core banking platform with generative AI at its core using Google Cloud Vertex AI and Model Garden APIs.
Leveraged Google Cloud services like BigQuery, Cloud SQL, Dataflow, Pub/Sub, Cloud Run, and Kubernetes for data management, analytics automation, and scalable infrastructure.
Enabled engineering teams to directly interact with AI models for predictive decision-making without infrastructure complexity.

Technologies

Vertex AI Model Garden BigQuery Cloud SQL Dataflow Pub/Sub Cloud Run Kubernetes

Accelerated product development and innovation through integrated generative AI capabilities.
Reduced manual data science scripting through automated analytics with BigQuery.
Improved operational efficiency and achieved cost savings.
Positioned Pave Bank as a technology-driven financial services innovator.

Sources & evidence1

Evidence: Medium55/100Evidence strength