bunq

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bunq has 2 source-linked AI deployments documented in AIUseCaseHub, across 1 industry and 1 country.

Use Cases

2

Industries

1

Countries

1

Hyperscaler mix

See whether bunq's cases are powered by Microsoft, AWS, GCP, or multiple providers.

How bunq builds AI

Build / Buy / Compose across this company's documented cases

BuildBuyComposeMixed

2 of 2 cases classified (100%) · Compare all use-case types

Use case portfolio

Use case types at bunq

Customer service automation leads with 1 of 2 documented cases; 2 distinct types appear across the visible portfolio.

Reported outcomes

2 cases report measurable results

+90%

Quality & accuracy

median · 1 metric

+82%

Automation & deflection

median · 1 metric

Medians of results published in bunq cases, normalized for comparability. See all benchmarks →

Technology snapshot

What bunq uses across visible cases

AI Agents appears in 1 of 2 indexed cases; 9 named technologies are mentioned, led by Amazon Bedrock.

All Use Cases (2)

bunq: Tripled user support efficiency using Amazon Bedrock on AWS

bunq is a digital bank serving more than 11 million users across Europe and operating a banking license in the Netherlands.To support growth and compliance requirements, bunq migrated its infrastructure to AWS and used managed services to simplify operations and scale quickly.The bank adopted Amazon Bedrock for generative AI use cases, including summarizing new user data and removing manual document-processing steps in onboarding and support workflows.

Finance

bunq: Multi-agent generative AI assistant on Amazon Bedrock to handle 97% of support

bunq, Europe’s second-largest neobank, upgraded its in-house generative AI assistant Finn to improve multilingual customer support and automate banking operations while maintaining security and compliance requirements.The solution uses Amazon Bedrock with Anthropic Claude models, Amazon ECS for orchestrator and agent services, Amazon DynamoDB for memory and conversation history, Amazon OpenSearch Serverless for vector search in RAG, and Amazon S3 for document storage.bunq redesigned the assistant around an orchestrator agent and an agent-as-tool pattern so primary agents can dynamically invoke specialized tools for tasks such as transaction analysis, document retrieval, failed payment handling, and image/document recognition.

Finance
AgentMulti-agentRAG

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