Automate Your IT Operations with Algomox AIOps.

Algomox AIOps is the next-generation approach that enables the automation of IT operations. The implementation of AIOps helps automatically identify unknown issues and anomalies from a huge volume of IT data using real-time advanced machine learning. This helps in providing actionable insights of data and enables the IT team to resolve them quickly. Algomox AIOps helps in revolutionizing IT operations to the next level.

AI based IT Infrastructure Automation

Algomox AIOps Platform helps in empowering IT automation. Enables in collecting raw data and turning them into actionable insights. Then applies AI and machine learning analysis to perform anomaly detection, event correlation, incident recognition, root cause analysis, and more. Algomox AIOps is the one-touch solution for all your IT automation.

Elements of Algomox AIOps Platform

Going beyond Observing. Turning data into actionable insights. Automatic correlation of events into meaning incident. Perform auto-remediation or auto-fulfillment to enable zero-touch resolution.


This element helps in the collection of every business and IT data from multiple data sources. We are using advanced machine learning and artificial intelligence capabilities to automatically detect any unknown anomalies or events. Observability helps in consolidating every monitoring tool into a unified platform. The element is capable of performing multivariate KPI anomaly detection and cross-domain log anomaly detection. Apart from that, it can intelligently perform incident recognition and identify the root cause of the problem.

AI based Observability


The engage is an Algomox AIOps element that enables in the complete automation of IT service and helpdesk activities and supporting IT user engagement. The engagement module helps in automatically creating IT tickets from omni-channel sources such as emails, chat, tools, and voice interactions. Apart from this, the engagement module enables to provide better IT ticket lifecycle management and AI-driven SLA management.

AI based Engagement Console


The action element of Algomox AIOps is where the zero-touch resolution takes place. The action element is capable of auto-healing every IT ticket that is created. The element initiates workflows capable of performing auto-remediation and auto-fulfillment of IT incident tickets and service request tickets. This enables IT operations team to focus on strategic tasks which enable them to innovate more.

AI based Automation Engine


Govern is an Algomox AIOps element that provides end-to-end visibility of entire IT operations and investment from business perspective. The governance helps monitor and correlate business metrics to IT metrics, thus enabling CIOs to effectively communicate IT value to the rest of the organization. CIOs could get a single pane of glass view, allowing them to govern IT operations effectively.

AI based IT Dashboard

Benefits of Algomox AIOps

Applying advanced AI and ML analytics and automation to IT Operations.

Cut down up to 80% of data science development time with advanced Feature Engineering
Intelligent Observability
Providing end-to-visibility of the entire IT organization enables in turning data into actionable insights, thus performing anomaly detection by applying advanced ML.
Cut down up to 80% of data science development time with advanced Feature Engineering
Automated Incident recognition and root cause analysis
Diagnose and correlate events into one actionable incident and identify the root cause of the problem, thus intelligently alerting the IT operators.
Cut down up to 80% of data science development time with advanced Feature Engineering
Reducing MTTR
Automated ticket resolution employing auto-remediation or auto-fulfillment of incident and service request tickets, thus keeping the SLA intact and reducing MTTR to 60%.
Cut down up to 80% of data science development time with advanced Feature Engineering
Left shift further with L1 Automation
Applying AI-driven mechanism to automate IT helpdesk activities without the intervention of manual effort. This enables reducing manual lean shits, operate 24x7, and also reduces MTTR.
Cut down up to 80% of data science development time with advanced Feature Engineering
Automated Patch Management
Automatic identification of new patch releases is made possible with AIOps. The risk score of each patch can be automatically identified using an advanced machine learning algorithm.
Cut down up to 80% of data science development time with advanced Feature Engineering
Monitoring Tool Consolidation
Consolidating every monitoring tool into a single and unified platform for better results and ease of operations and providing 100% visibility into every IT metric such as KPIs, logs, and traces.

Your AIOps Roadmap.

AIOps Roadmap
1. Reactive

This is the starting stage of AIOps in any organization. Organizations having traditional monitoring tools usually that are working on a reactive mode. The IT team receives thousands of events every day from the chatty monitoring tools and struggle to figure out where to focus.

2. Proactive

In this level, AIOps tools and processes can quickly determine the root cause and notify the IT operations team. This will help the IT operations team to take quick action before the problem is noticed by the end-users. Also, it reduces the impact on business operations.

3. Predictive

This is the third level with more analytics to foresee future events like service outage or infrastructure capacity exhaustion with a high degree of probability. An AIOps platform provides predictive recommendations to the IT operations team to minimize or eliminate business impacts.

4. Prescriptive

IT organizations at this prescriptive level can get prescriptive recommendations from the AIOps systems and can make better and faster-informed decisions. This will enable them to be a better agile organization to deal with the fast-moving business requirements with the highest level of efficiency.

5. Automative

The automated IT organization can leverage an advanced AIOps platform that can provide resource optimization and auto-remediation recommendations to the automation platform based on AI- based analytics and keep the system up and running without much human intervention.