MLCostIntel

What it does

Most cloud cost tools treat AI workloads like any other compute resource, making it hard to understand where AI spending comes from. MLCostIntel is purpose-built for AWS AI/ML workloads, delivering end-to-end cost intelligence across Amazon SageMaker, Amazon Bedrock, Amazon EKS, GPU infrastructure, storage, and networking. It attributes AI costs, identifies optimization opportunities, detects anomalies, and continuously monitors AI infrastructure spend.

Optimize AI infrastructure costs on AWS. MLCostIntel unifies Amazon Bedrock, SageMaker, GPU, and LLM API spend into one FinOps platform — attribute every dollar to teams and models, detect waste, forecast, and cut AI cloud costs. Free assessment on AWS Marketplace.

MLCostIntel attributes every dollar of AWS spend across the full AI/ML stack — training, inference, generative AI, document AI, and AI-supporting infrastructure . Full-stack visibility, anomaly detection, and a prioritized roadmap to optimize every layer of your AI footprint. Built for ML Platform Engineers, VP Engineering, and FinOps teams running AI on AWS. They lump training, inference, Bedrock, and document AI into general compute — no attribution by workload, no visibility into the supporting infrastructure AI depends on. You see compute and a bit of GPU. You don't see training vs. inference vs. generative AI vs. the data and networking that support them. Decisions get made…from mlcostintel.com

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