Context
- A European fintech needed a distributed AI platform with production-grade MLOps. In a regulated business, a model that ships without monitoring or a way back is a risk they could not carry, so every model had to come with operational scaffolding.
Approach
- Designed an eight-service distributed architecture.
- Built MLOps pipelines for training, serving, and evaluation.
- Ran it on GKE and BigQuery at scale.
What we built
- Distributed AI fintech platform.
- MLOps pipelines with evaluation and rollback.
- Vertex AI integration across services.
Results
- A platform where models ship with operational scaffolding.
- Distributed scale on GCP.
- AI the business can actually run.
Stack & standards
Vertex AIGKEBigQuery
Model governanceSOC 2SRE
“MLOps done properly. Our models ship with monitoring and a way back, every time.”
European AI Fintech engagement
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