01
Batch workloads
Reduce input load on repetitive tasks such as classification, inference and reporting.
AETHER · High Volume
Small unit savingscreates a huge impact on scale.
In production environments where millions of tokens are processed, unnecessary context carried in every request directly turns into a capacity and cost problem.
Scale Management
Systematic optimization for heavy LLM traffic.
Add Aether to high-volume call paths to manage token usage under a measurable policy across the application.
02
Heavy RAG traffic
Optimize the portion of large document sets returned in each query that reaches the model.
03
Traffic policies
Apply separate optimization targets for different endpoints and customer segments.
04
Capacity planning
Use token savings metrics in budget, quota and provider capacity decisions.
Application Flow
01
Create a baseline
Measure current token consumption by route, model and use case.
02
Open controlled traffic
Enable optimization on selected calls and compare the difference in quality and cost.
03
Scale policy
Gradually apply proven settings to larger traffic segments.
Smaller context. More controlled AI cost.
Contact our team to add Aether Compress to your current LLM workflow.