Company intelligence
nOps
nOps provides automated cloud cost optimization and comprehensive visibility solutions for AWS, GCP, and Azure.
About nOps
nOps’ automated multi-cloud cost optimization platform cuts cloud costs by up to 55%+ vs. on-demand pricing - without operational overhead or long-term lock-in. Managing $4B+ in annual cloud spend for 600+ customers, nOps is an AWS Advanced Technology Partner, FinOps Foundation Premier member, and G2 High Performer for Cloud Cost Management. Customers receive a free savings analysis and begin realizing savings within 2 to 4 weeks. The Commitment Management solution uses a share-of-savings business model that incentivizes nOps to help its customers save money. nOps platform includes: Commitment Management: autonomous rate optimization for AWS, Azure, GCP to maximize savings and flexibility Cost Visibility & Allocation: Understand which teams, products and features are driving spend for Multicloud, AI, Kubernetes, and SaaS — with anomaly detection, budgeting, forecasting and reporting AI Insights: analytics and optimization recommendations for token usage, model substitution, cache optimization, provisioned throughput and batch processing The time to value is 30 minutes to get started and receive a Free Savings Assessment. Follow us on Twitter @nopsio
Verified activity
Signals from nOps
14 published signals
Products & Services
nOps learned that Google Cloud benchmarks the unit economics of LLM workloads.
Reported by nOps
Products & Services
nOps learned that Google Cloud adds token-level observability for data agents.
Reported by nOps
Products & Services
nOps learned that Amazon CloudFront flat-rate plans can now be managed through AWS APIs, CLI, SDKs, CloudFormation, and CDK, making it easier to automate a predictable monthly pricing model covering CDN, WAF, DDoS protection, DNS, logging, and edge compute.
Reported by nOps
Products & Services
nOps learned that AWS added serverless diagnostics to its MCP Server, letting AI coding agents investigate Lambda functions and related resources in a single operation instead of orchestrating multiple API calls — reducing the token usage required for troubleshooting.
Reported by nOps
Research & Knowledge
nOps learned that Microsoft published new guidance on how context engineering decisions affect the cost of running enterprise AI agents at scale.
Reported by nOps
Presence & Recognition
nOps team spent a day at the US Open in NYC, joining AWS and a small group of partners for the Men's and Women's 2nd Round matches at Arthur Ashe Stadium.
Reported by nOps
Presence & Recognition
nOps attended the AWS Marketplace Sellers Conference in Seattle and met key members of the AWS Marketplace team.
Reported by Chintu P.
Products & Services
nOps highlights that AWS Lambda now automatically detects and stops recursive invocation loops across all commercial AWS Regions.
Reported by nOps
Products & Services
nOps highlights that the FinOps Foundation updated its guidance for applying the FinOps Framework to streaming and real-time data platforms.
Reported by nOps
Products & Services
nOps highlights that the FinOps Foundation published a new framework for how FinOps for AI and Tokenomics fit together: FinOps handles budgeting, ownership, allocation, and accountability, while Tokenomics focuses on technical AI efficiency decisions such as model selection, caching, cost per outcome, and product economics.
Reported by nOps
Products & Services
nOps highlights that Microsoft outlined four optimization levers in Foundry: model routing, caching, prompt and agent optimization, and observability.
Reported by nOps
Products & Services
nOps highlights that Microsoft added Cost Management tools to Azure Resource Manager MCP, allowing AI agents to query Azure cost data directly alongside infrastructure operations.
Reported by nOps
Products & Services
nOps highlights that Google Cloud published new guidance for dynamically managing AI compute capacity using flex-start scheduling, automated hardware fallback, and granular GPU/TPU allocation.
Reported by nOps
Products & Services
nOps highlights that AWS published a new approach for using SQL-based filtering directly in AWS Data Exports, letting teams generate CUR 2.0 datasets for specific accounts, services, regions, cost categories, or tags without building a separate downstream ETL pipeline.
Reported by nOps