I will reduce your amazon bedrock and genai infrastructure costs

Did your AWS bill explode after launching your Generative AI or RAG application? Traditional FinOps strategies don't work for AI. LLM inference costs and the "Agentic Cost Multiplier" require specialized architectural tuning.

As an Enterprise Cloud Architect and AI FinOps expert, I will restructure your AI data flows to drastically cut your AWS Bedrock bills without degrading application latency or output quality.

How I optimize your AI costs:

• Prompt Caching: Restructuring your payloads to cache system prompts, cutting input token costs by up to 90%.
• Intelligent Prompt Routing: Dynamically routing simple tasks to cheaper models (like Claude 3 Haiku) and saving premium models for complex reasoning.
• RAG Right-Sizing: Migrating expensive, over-provisioned vector databases (like default OpenSearch Serverless) to cost-effective alternatives (like S3 Vectors) if ultra-low latency isn't required.
• Batch Inference: Moving asynchronous tasks to batch APIs for massive cost reduction.

FR Speakers: Je suis francophone. Discutons en français de l'optimisation de vos factures cloud et de votre architecture IA !