AIops Maturity Models
Level 1: Reactive
Events and logs are collected for reactive purposes. Teams work through siloed operations with little to no dialogue with the business and are constantly solving problems to keep the business running.
Level 2: Integrated
Silos begin to break down and dialogue happens. Data sources are integrated into a unified architecture, and overall ITSM processes improve. Additionally, ML and AI begin to layer into the overall process.
Level 3: Analytical
Teams have more defined baseline metrics, processes see improvements with more AI and ML capabilities. Here data is available, and metrics become more measurable, IT teams are able to show the overall business value.
Level 4: Prescriptive
Teams begin implementing ML and Automation, giving them access to more analytics and data to track overall improvements. Additionally, a more optimized ITSM process with human interaction is put into place.
Level 5: Automated
There is full automation with no human interaction, and teams are able to leverage ML based on prescriptive and predictive models. This provides full transparency across all levels of the business operating proactively rather than reactively.
Business services with visibility and AI Operations
Operational Intelligence
Transform user experience & improve efficiencies by correlating data and combining analytics with automation to resolve issues faster.
Infrastructure Monitoring
Proactively and efficiently managing your private and public cloud, infrastructure, and applications utilising AI/ML.
Network Monitoring
Gain unified, scalable AI-driven network monitoring for traditional, SDN and cloud networks.
Automic Automation
Drive faster, automated issue remediation with integrated intelligent automation.