FinOps for AI

Token Optimizer is a professional services offering that helps organizations optimize Generative AI operating costs for workloads built on Amazon Bedrock, AWS AI services, and custom GenAI applications running on AWS. The service analyzes prompts, AI applications, agentic workflows, RAG pipelines, and instruction sets to identify unnecessary token consumption, recommend optimizations, and estimate potential cost savings across foundation models available through Amazon Bedrock and other supported models deployed on AWS.

Designed for AI Engineering, Platform Engineering, and FinOps teams, Token Optimizer provides actionable recommendations, optimized prompt versions, cost projections, and measurable savings reports to improve AI efficiency while maintaining response quality and business outcomes.

Key Benefits Reduce token consumption and operating costs for Amazon Bedrock-based applications Identify inefficiencies in prompts, RAG pipelines, AI agents, and orchestration workflows running on AWS Optimize prompt design, context management, and model routing strategies Compare cost implications across foundation models available through Amazon Bedrock Generate engineering and FinOps reports with quantified savings opportunities Improve governance and operational efficiency for enterprise GenAI deployments on AWS Core Capabilities AWS GenAI Workload Assessment

Assess Generative AI solutions deployed on AWS, including applications built using Amazon Bedrock, serverless architectures, containerized AI services, and custom LLM integrations.

Intelligent Workload Classification

Analyze and classify:

Amazon Bedrock-based AI applications RAG implementations using AWS services Agentic AI systems Prompt chains and orchestration workflows Enterprise GenAI solutions hosted on AWS Optimization Recommendations

Provide recommendations for:

Prompt engineering and token reduction Context window optimization Foundation model selection and routing Agent orchestration efficiency RAG architecture optimization AI governance and FinOps best practices Optimized Prompt and Instruction Rewrites

Generate optimized prompt and instruction versions with side-by-side comparisons, helping teams validate savings and performance improvements before implementation.

Cost and Savings Analysis

Deliver visibility into:

Current token consumption Optimized token consumption Estimated cost savings Additional optimization opportunities Projected return on investment Deliverables AWS GenAI workload assessment report Token consumption analysis Prompt optimization recommendations Cost reduction projections for Amazon Bedrock workloads Implementation roadmap and best practices Executive and FinOps savings summary Associated AWS Services Amazon Bedrock AWS Lambda Amazon ECS / EKS Amazon S3 Amazon OpenSearch Service Amazon DynamoDB AWS Step Functions Amazon API Gateway AWS CloudWatch Business Outcome

Organizations can improve the cost efficiency of their Amazon Bedrock and AWS-based Generative AI solutions by reducing unnecessary token consumption, optimizing model utilization, and establishing repeatable AI cost-governance practices.