Semantic Caching
Intercepting repetitive queries and serving cached responses based on semantic similarity, bypassing the LLM API entirely.
LLM Economics & Inference Optimization
Generative AI scales compute costs exponentially. We implement advanced token telemetry, semantic caching, and router models to drastically reduce API burn rates without sacrificing output quality.
Controlling the Exponential Cost Curve
Deploying generative AI to thousands of employees or customers rapidly leads to uncontrolled API expenditures. We conduct deep architectural reviews of your existing AI implementations to identify token waste and inefficient prompt loops.
Optimization Strategies
Prompt Compression
Algorithmic reduction of prompt context windows, ensuring the model only receives the exact tokens required for the task.
Inference Infrastructure
For open-weights models, we optimize inference engines (using vLLM, TensorRT-LLM) to maximize throughput and minimize latency.