Operations | Monitoring | ITSM | DevOps | Cloud

Managing the cost of foundation models is a critical challenge as AI adoption surges, particularly for teams using powerful models like Anthropic's Claude Opus and Claude Sonnet. Growing teams generate larger prompt volumes and escalating model complexity, making it difficult to have clear visibility, accountability, and control of cloud AI spending.

AI coding assistants are already transforming how developers work, helping them write code faster, answer tough questions, and automate repetitive tasks. It’s exciting, it’s powerful… and it’s just the beginning. Cortex MCP connects your AI assistant directly to your live service data, ownership, and organizational standards so it can give accurate, context-rich answers right in your IDE.

‍ The ilert AI Voice Agent is designed to transform how on-call engineers handle urgent calls. Instead of waking engineers at 3 a.m. with minimal context, the AI Voice Agent collects essential details first and routes calls intelligently based on relevant, up-to-date information. ‍ The agent works hand in hand with ilert’s Call Flow Builder – a visual tool that lets users design custom call flows by connecting configurable nodes.

Our CLI team has been cooking up some awesome new AI functionality that we think you will love. The latest release includes several new commands such as changelog, commit, pr, and a command to check the remaining tokens on your subscription. They are all nested under a new top level command, gk ai.

Natural language copilots are one of the most exciting developments in AI for network operations. They allow engineers and operators to query complex environments in plain language rather than memorizing obscure CLI commands or digging through multiple dashboards. But here’s the truth: a copilot is only as good as the AI behind it. Without a purpose-built network LLM, a copilot can’t deliver the accuracy, context, and speed that real-world IT operations demand.

AI adoption isn’t just accelerating, it’s compounding. From GPT-5 to Claude to Llama and beyond, engineering teams are integrating diverse LLMs across products, experiments, and services. And finance teams are now grappling with a new kind of cloud complexity: token-based economics and volatile inference costs, often spread across multi-model, multi-cloud, and multi-region architectures. The modern FinOps stack needs to keep up. CloudZero was built for this moment.