Sector
SaaS
72% LLM cost optimisation on a global SaaS platform
The customer quotes and brand details below are representative content, prepared to show the structure of the template.
The challenge
As user numbers grew, monthly API token bills and GPU rental budgets got away from the company.
Our approach and integration
We built a layer that inspects incoming queries and applies semantic caching and dynamic routing. Similar questions are answered straight from a Redis cache; simple queries go to small models and complex ones to large models.
Results and impact
A direct 72% saving on total AI infrastructure and API cost.
Cache-served queries answer in 15 milliseconds instead of 1.5 seconds.
No measurable loss in user experience or answer quality.
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