Operations | Monitoring | ITSM | DevOps | Cloud

Cybercriminals are no longer lone hackers sitting behind screens; they use artificial intelligence to supercharge their attacks. They employ large language models (LLMs) that generate phishing content to evade human detection. They use malware that adapts mid-execution to bypass sandbox environments and deepfake video/audio to mimic executives in real time.

Every second counts when it comes to detecting, diagnosing, and resolving network incidents, yet many teams still find themselves stuck in reactive mode, drowning in alerts, manually writing scripts, and managing tickets across disconnected systems. This is where Selector and Itential come in. Together, Selector and Itential deliver a powerful, enterprise-ready solution that closes the loop between detection and action.

AI is changing how we build software — but debugging code still comes down to having context. One minute the model’s performance is cruising. The next, you’re hit with a KeyError from a tool you forgot existed, triggered by a model that silently timed out, and a retrieval call that returns... nothing, or 11 “Let me try this a different way" messages before failure. You’re stitching together LLM calls, agents, vector stores, and custom logic. Then hoping it holds up in prod.