AI Infrastructure Cost Optimization Stack

Unified API gateway aggregating 200+ models with pay-as-you-go pricing. Eliminates vendor lock-in and enables cost comparison across LLM providers by routing requests to cheapest available model matching performance requirements.

Observability platform tracking LLM call costs, token usage, and latency patterns. Identifies expensive operations and usage anomalies to guide auto-scaling decisions and cost optimization strategies.

Serverless GPU platform billing per second with zero idle costs. Auto-scales to zero when unused, perfect for startup workloads with variable demand. Eliminates reserved capacity waste.

Edge serverless platform with built-in Workers AI for inference at the edge. Reduces latency and bandwidth costs by processing requests closer to users without cold starts.

Data orchestration with asset-based lineage tracking. Monitors compute resource usage across ML pipelines and enables intelligent scheduling to batch jobs during off-peak hours for cost savings.

Model and data versioning prevents redundant retraining and storage. Tracks which model versions are actually used in production, eliminating costs from unused model variants.