AIOps and Machine Learning Architecture with Selector AI

Watch a 24-minute technical presentation from Cloud Field Day 22 exploring the architecture and functionality of Selector AI's AIOps platform. Learn how the platform leverages machine learning techniques for data ingestion and analysis, processing raw metrics, events, and syslogs to understand network behavior without content generation. Discover the platform's ML-driven approach focusing on accuracy through regressions, clustering, and cosine similarities while avoiding LLM hallucinations. Explore how the declarative ETL and compiler enables flexible data ingestion from diverse sources including legacy devices, cloud services, and custom files. Understand the Kubernetes-based architecture that ensures horizontal scalability and creates context through CMDB data and metadata integration. See how generative AI enhances user experience by translating natural language queries and JSON outputs while maintaining accuracy as a complementary tool. Gain insights into the platform's adaptability with various LLMs and its ability to learn specific network infrastructure details over time, supported by comprehensive customer support throughout implementation.