A Day in the Life of the Enterprise Administrator with Selector AI

Selector AI’s presentation at Cloud Field Day 22, delivered by VP of Product Sachin Natu, focused on illustrating a typical day for a cloud engineer managing Fortune 500 company environments. Natu highlighted the significant challenges these engineers face, emphasizing the complexity arising from the multitude of technologies, administrative domains, and siloed views across on-premise networks, multiple ISPs, and hybrid cloud deployments. The core problem showcased was the difficulty in troubleshooting even a seemingly simple issue like a malfunctioning chatbot, requiring investigation across numerous interconnected systems and data sources.

The presentation centered around Selector AI’s platform, which aims to address these complexities by providing a Slack-native AI-powered interface. Using a scenario involving a chatbot outage, Natu demonstrated how the platform proactively identifies problems, correlates events across various systems (including network devices, ISPs, and cloud services), and provides actionable recommendations within the Slack workspace itself. The platform doesn’t simply identify issues; it also offers contextual information, such as historical data and user-added notes, to build a clear picture of the situation, allowing for more efficient and informed decision-making.

Crucially, Natu differentiated Selector AI’s approach from generative AI, emphasizing the platform’s reliance on machine learning techniques for accurate data analysis and correlation, rather than generating hypothetical solutions. While leveraging Large Language Models (LLMs) for natural language interaction, the core of the platform uses precise data analysis to ensure accurate representations of the systems being monitored. This approach addresses concerns about the reliability of AI-driven insights in critical infrastructure management and ensures that the recommendations provided are grounded in factual data and historical context. The presentation concluded with a planned deeper dive into the platform’s architecture and data processing methods.