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    SNS Managed AI Operations - MLOps and AI Cost Governance on AWS

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    AI in production is an operations problem, not a project. SNS operates your models, agents and data pipelines under SLA and reports what every inference actually costs. The service covers deployment pipelines, drift monitoring, retraining and guardrail tuning on Amazon SageMaker AI and Amazon Bedrock, with observability through Amazon CloudWatch and Amazon Managed Grafana. The AInomics layer allocates token and GPU spend per application, team and use case, then reduces it through right-sizing, caching, model routing, batch inference and Savings Plans.

    Overview

    The second year of an AI programme is where most value is lost. Models drift, guardrails are never tuned, retraining is postponed, and the inference bill arrives without anyone being able to say which application caused it. Finance then declines to fund the next use case, not because the first one failed, but because nobody can explain its unit economics. This managed service takes ownership of both problems: operations and cost.

    On the operations side, SNS runs deployment pipelines, model registry, drift and quality monitoring, scheduled retraining and guardrail tuning across Amazon SageMaker AI and Amazon Bedrock under agreed service levels. Changes to models and agents follow a controlled release process with rollback, keeping every version traceable for audit. Observability covers latency, error rates, throughput, guardrail interventions and answer quality through Amazon CloudWatch, AWS X-Ray and Amazon Managed Grafana, with alerts routed to the SNS service desk. On the cost side, the AInomics layer allocates token, inference and GPU spend to individual applications, teams and use cases, then drives it down through right-sizing, prompt caching, model routing, batch inference and commitment-based discounts. Showback and chargeback reporting is delivered monthly and correlated with your own business KPIs.

    Onboarding takes four to six weeks, after which the service runs as a rolling subscription with monthly reporting in German or English. This service relates to the following AWS services: Amazon SageMaker AI including Pipelines, Model Registry, Model Monitor and Clarify, Amazon Bedrock including application inference profiles, evaluations, invocation logging and Guardrails, Amazon CloudWatch, AWS X-Ray, Amazon Managed Grafana, Amazon Managed Service for Prometheus, AWS Cost Explorer, AWS Budgets, AWS Cost and Usage Report, AWS Cost Optimization Hub, AWS Compute Optimizer, AWS Trusted Advisor, AWS Systems Manager, Amazon EventBridge and AWS Step Functions. Tiered service levels are available, up to 24/7 coverage.

    Highlights

    • Operations under SLA, from an Austrian service desk. SNS runs deployment pipelines, model registry, drift and quality monitoring, scheduled retraining and guardrail tuning across Amazon SageMaker AI and Amazon Bedrock, with controlled releases and rollback so production AI behaves predictably.
    • AInomics: cost per application, team and use case. Token, inference and GPU spend is allocated using Amazon Bedrock application inference profiles, AWS Cost and Usage Report and AWS Cost Explorer, then reduced through right-sizing, prompt caching, model routing, batch inference and Savings Plans.
    • Monthly reporting against your KPIs, in German or English. Technical performance, guardrail interventions, answer quality and cost are correlated with the business metrics you care about, giving finance and IT a shared basis for approving the next use case.

    Details

    Delivery method

    Deployed on AWS
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    Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.

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    Support

    Vendor support

    SNS offers a wide range of Cloud Solutions, Professional Service and Managed Services options for Customers. For more information please visit http://sns.at/  Phone: +43 (0) 5 / 06 333 Email: aws@sns.at