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Enterprise Layer Intelligence
Categories/DevOps & CI/CD/nOps
nOps

nOps

Founded 2017

Automate cloud cost reduction and commitment management across multiple clouds

Pricing model

Demo

You can use nOps to track and reduce your cloud and AI infrastructure spend automatically. The service connects to your cloud accounts and continuously buys and rebalances commitments like Reserved Instances and Savings Plans to cut costs without manual effort. It also tracks AI spending across models like Claude, Cursor, and Bedrock down to specific features and teams. You get clear dashboards showing your effective savings rates, anomaly detection, and unified reports across multicloud, Kubernetes, and SaaS environments.

What nOps does

Connect cloud accounts using read-only permissionsAnalyze historical usage patterns to plan discount strategiesAutomate the purchasing and selling of compute commitmentsMap AI model token usage back to specific engineering teamsSet up cost anomaly alerts for unusual spending spikesGenerate unit economics reports for executive leadershipCalculate effective savings rates across compute instancesAutonomous hourly commitment management for cloud discountsMulti-cloud support covering AWS, Azure, and Google Cloud PlatformDetailed AI cost allocation across models, tokens, and teamsAutomated purchase and rebalancing of Reserved Instances and Savings PlansRead-only connection without requiring infrastructure changes or agentsReal-time tracking of Effective Savings Rate and discount coverageFinOps assistant agent to answer billing queries and automate tasksReal-time cost anomaly detection and forecasting dashboards

Pricing breakdown

Pricing model: Book a demo

Frequently asked

AWSAWSMicrosoft AzureMicrosoft AzureKubernetesKubernetesCursorCursorClaudeClaudeOpenAIOpenAI

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nOps, cloud cost management, FinOps, AWS cost reduction, Azure savings, GCP commitment management, Reserved Instances, Savings Plans, Kubernetes cost allocation, AI cost tracking, cloud spend forecasting, anomaly detection, cloud billing optimization