Temperstack is an advanced AI-powered Site Reliability Engineering (SRE) platform that revolutionizes how organizations manage their infrastructure and application reliability. It integrates with your existing monitoring tools to provide comprehensive visibility and automated response capabilities across your entire technology stack. The platform goes beyond traditional monitoring by combining artificial intelligence with SRE best practices to proactively identify, prevent, and resolve potential service degradation and downtime before they impact end users. Through its intelligent automation and AI-driven insights, Temperstack helps organizations maintain optimal service levels while reducing operational overhead and alert fatigue. Features : Automated Discovery Engine: Automatically identifies all infrastructure and application components requiring monitoring Alert Comprehensiveness (ALCOM) Score: Measures and tracks monitoring coverage from 0-100 Automated Alert Setup: Programmatically deploys missing alerts based on best practices Continuous Monitoring Maintenance: Daily scans detect disabled alerts and new resources Alert Optimization: AI-driven threshold adjustment to reduce false positives while maintaining coverage Service Mapping: Auto-discovers and groups related infrastructure and applications Team Schedule Management: Manages rotation schedules and shift policies across time zones Multi-Channel Integration: Routes alerts through email, Slack, Microsoft Teams, and WhatsApp Escalation Management: Configures and enforces escalation rules for unresponsive scenarios Context Enrichment: Provides troubleshooting guidelines and system context with each alert Dynamic Runbooks: Auto-generates and updates resolution guides based on system changes Root Cause Analysis (RCA) tool: Standardises RCA capture & tracks resultant actions to completion Knowledge Base: Codifies tribal knowledge and learns from successful resolutions Pattern Recognition for accelerated root cause identification: Suggests probable root causes based on historical incidents