Artificial Intelligence · 10.08.2026, 16:55 UTC
How nOps shipped FinOps agents 75% faster with Amazon Bedrock AgentCore
| Schweregrad | info |
|---|---|
| Kategorie | Artificial Intelligence |
| Quelle | AWS Machine Learning ↗ |
| Veröffentlicht | 10.08.2026 UTC |
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nOps, an AI-powered cloud optimization solution, recently reimagined its Financial Operations (FinOps) analytics capabilities by transitioning to Amazon Bedrock AgentCore. Amazon Bedrock AgentCore is a service to build, connect, and optimize agents at scale, with any framework or model. The new foundation helps nOps better serve customers managing commitment optimization across Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Through continual optimization of commitments such as Reserved Instances and AWS Savings Plans, nOps helps teams maximize savings, reduce risk, and automate away the operational burden of manual FinOps. Today, nOps supports customers representing more than USD $4 billion in cloud spend under management. In this post, we explain how nOps transitioned our analytics and agent experience to accelerate product delivery, improve response quality, and reduce operational complexity using Amazon Bedrock AgentCore, Databricks Lakehouse Metric Views, Databricks Lakebase, Amazon DynamoDB, and Vercel. Scaling FinOps AI beyond the limits of API-centric infrastructure As we expanded our product portfolio and customer base, the infrastructure, front-end, and back-end teams needed to support increasingly complex analytics workflows while maintaining high reliability and multi-tenant isolation. Existing infrastructure patterns introduced friction: Response latency and inconsistency: Long context messages from API-based data access increased latency and reduced response consistency. System complexity: Multiple orchestration and …