BNexora: A Next-Generation AIOps Platform for Cognitive Observability and Autonomous Maintenance

BNexora is a next-generation agentic Artificial Intelligence for IT Operations (AIOps) platform that integrates cloud observability, automated root cause analysis, business impact assessment, predictive alerting, and semantic security analysis into a unified intelligent monitoring framework. The platform is designed to bridge the gap between infrastructure telemetry and business decision-making by combining lightweight telemetry collection with Large Language Model (LLM)-based cognitive reasoning. BNexora employs a three-layer architecture consisting of a lightweight telemetry collection layer, an asynchronous aggregation and routing layer, and an AI-powered cognitive intelligence layer. The system automatically analyzes logs, metrics, traces, and application context to identify root causes, estimate business impact, generate remediation recommendations, and produce executive-level operational summaries in near real time. The platform also incorporates role-based access control, deterministic revenue-loss modeling, predictive failure detection, and semantic dependency security analysis to improve operational reliability and decision support. The paper presents the complete architecture, mathematical models, implementation methodology, and experimental evaluation of BNexora. Controlled experiments on a staging cloud environment demonstrate significant reductions in diagnostic latency while maintaining a lightweight resource footprint. The results indicate that integrating agentic AI with modern observability systems can substantially improve incident response efficiency and accelerate the transition from reactive monitoring toward cognitive and semi-autonomous IT operations. This work contributes to the fields of AIOps, intelligent observability, cloud operations, and AI-assisted infrastructure management by providing a practical and extensible framework for next-generation autonomous maintenance systems. Keywords: AIOps, Agentic AI, Cloud Observability, Large Language Models, Root Cause Analysis, DevOps, Site Reliability Engineering, Cloud Monitoring, Predictive Maintenance, Business Impact Analysis, Semantic Security Analysis, Autonomous IT Operations.