AWS · Financial Services
Top-5 US bank launches production GenAI on AWS Bedrock in 14 weeks
40% TCO reduction · 14-week launch from kickoff to GA
At a glance
Key metrics
Challenge
The situation
Self-hosting LLMs for internal knowledge assistants was expensive and slow to iterate. The bank wanted a governed pattern it could repeat across lines of business.
Approach
How we delivered
- 01 Defined a standard reference architecture on Bedrock + SageMaker with a bank-wide governance layer.
- 02 Built a GenAI platform team that owned the shared rails; lines of business brought use cases, not plumbing.
- 03 Shipped the first production use case in 14 weeks, then cloned the pattern.
Architecture
Solution architecture
Amazon Bedrock for foundation-model access; fine-tuning via Amazon SageMaker. Retrieval on Amazon OpenSearch Serverless. Guardrails via Amazon Bedrock Guardrails with bank-specific policy layered on. Observability through Amazon CloudWatch + Bedrock model-invocation logs, aggregated for internal audit.
Outcomes
Measured results
- 40% TCO reduction versus the prior self-hosted LLM estate.
- 4 production use cases live within 6 months on the same governed pattern.
- Internal audit signed off on the shared control plane at first review.
Technology
Tech stack
GenAI
- Amazon Bedrock
- Amazon SageMaker
- Bedrock Guardrails
- Bedrock Knowledge Bases
Search
- Amazon OpenSearch Serverless
Observability
- Amazon CloudWatch
- Bedrock invocation logs
“We stopped running an LLM estate and started running a GenAI platform. Everything got faster and cheaper.”
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