Finance
Model training cycle down 40%, online inference cost down 50%
A quantitative investment firm
↓40%
Training cycle
↓50%
Inference cost
Background
The firm retrains models frequently and needed both faster iteration and lower serving cost.
Our approach
Training runs on rented GPU hours with checkpointed storage, while serving uses the inference engine’s batching and cache optimization.
Outcomes
↓40%
Training cycle
↓50%
Inference cost
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