Top 10 AIOps Companies in 2025

The future of IT operations won’t rely on humans alone - they rely on AI. With more complex IT systems, traditional monitoring can’t keep up. AIOps addresses these challenges by leveraging AI and machine learning to detect, predict, and resolve issues automatically. 

But implementing AIOps into these complex IT ecosystems poses challenges. That’s where AIOps companies come in. AIOps companies help organizations design, implement, and manage AI-driven IT operations for maximum reliability and performance.

This post will spotlight the top 10 AIOps companies in 2025, highlighting their expertise in implementing, managing, and optimizing their solutions.

What is AIOps?

AIOps stands for Artificial Intelligence for IT operations. It is a process that utilizes Big Data, artificial intelligence (AI), and machine learning to automate and enhance the management and monitoring of IT systems. 

It helps teams monitor systems, detect anomalies, resolve issues more quickly, and predict potential problems across complex IT environments.

How We Selected the Top AIOps Companies

Choosing the top AIOps companies requires a multifaceted approach that was designed to evaluate a company’s real-world value, technological capabilities, and market impact. Some of the key criteria that we have chosen to select the top AIOps companies are

• Years of experience: We have focused on the proven track record of each AIOps company on how they have delivered their projects in the AIOps service and IT operations space.
• AIOps service offerings: An AIOps company’s services must go beyond basic monitoring and include services such as Intelligent Data ingestion, event correlation and noise reduction, anomaly detection, predictive analysis, and automated root cause Analysis (RCA). This will say something about their applicability across various industries in how they handle IT operations.
• Integration and Interoperability: The AIOps platform should offer a wide range of pre-built integrations with IT monitoring, logging, and ISTM tools. An AIOps company should seamlessly integrate with the existing toolchain and avoid vendor lock-in.
• Client review and case studies: We have deeply looked into the company’s market value and rankings using major platforms like Clutch, Gartner, and G2.
• Pricing model: We have reviewed the pricing models to highlight companies that are accessible for all sizes of businesses.
• Technology usage and future-readiness: AIOps companies were analyzed on how they use the advanced AI/ML models, automation frameworks, and integrations to deliver measurable outcomes. The best AIOps companies will show their steep innovation curve. Leading AIOps platforms are now using generative AI to provide capabilities like intelligent incident summarization, suggested remediation steps, and natural language-based queries for data analysis. AIOps companies should also handle, scale, dynamism, and complexity of modern cloud and containerized environments.

Top AIOps Companies

1. Entrans

Entrans is a leading digital transformation and consulting firm that specializes in providing AIOps services through AI-led digital engineering. 

Key AIOps Services of Entrans

Entrans, as an AIOps service provider, transforms IT operations from a reactive to a proactive model.

• Ingestion and Data aggregation: This is a foundational AIOps service provided by Entrans. We collect data from diverse sources across an IT environment, including logs, metrics, traces, events, topology data, and network data. This step will normalize the data of all IT operations into a single file.
• Predictive analytics and Anomaly detection: We use historical and real-time data to forecast future issues such as imminent resource bottlenecks or system failures, enabling proactive intervention. This analysis will identify deviations from this baseline, such as a sudden spike in network latency, which may cause an issue to develop further.
• Event Correlation and noise reduction: One of the common challenges to be addressed in an IT environment is the overwhelming volume of alerts, leading to “alert fatigue”. Our Managed AIOps services use AI to group related alerts into a single incident and reduce notification noise.
• Root cause analysis and remediation: AIOPs automates and accelerates RCA by analyzing event correlations and dependencies across the IT stack. They can accelerate this by correlating data, finding the root cause, and giving suggestions. So when an incident happens, they enable automated responses to incidents, which include automated ticketing, triggering runbooks, and self-healing issues.
• Integration with cloud: Entrans provides AIOps solutions that can seamlessly integrate with existing monitoring, logging, and ITSM tools. We provide end-to-end IT visibility and avoid siloed systems.
• Consulting and Strategy services: We also provide consulting services to check whether the organization is ready to adopt AIOps by analyzing existing IT infrastructure, data sources, and operational maturity. We help in selecting the best AIOps tools and platforms available on the market in order to align with the business needs and cost.
• Performance optimization: We continuously refine the AIOps platform’s algorithms and automation rules to improve efficiency and reduce costs. We also provide training programs to our IT teams on how to effectively use the AIOps platform and interpret AI-driven insights.

How We built an AI agent Thunai using AIOps:

Thunai is a next-gen Agentic AI platform that was designed to transform organizational knowledge into autonomous AI agents capable of handling customer interactions, workflows, and data-driven tasks across support, sales, and marketing operations. 

Using AIOPs, we have developed Thunai, an AI agent that uses multimodal learning to process unstructured data like documents, audio, video, and chat transcripts, enabling real-time automation of complex processes. It has features like AI voice agents, AI chat agents, email agents, application agents, and self-learning orchestration capabilities.

2. Dynatrace

Dynatrace is the leading AIOps company. They offer a unified AI-powered platform with the help of the Davis AI core engine. They embed AI into every aspect of their platform, from data ingestion to automated remediation.

Key AIOps Services of Dynatrace

• Dynatrace’s Davis AI platform consolidated data silos across cloud, on-premises, and hybrid environments. They provide proactive issue prevention by detecting patterns, forecasting potential incidents, and operationalizing preventive measures in real time.
• Dynatrace’s platform includes capabilities for automated remediation with the assistance of generative AI. The platform’s answer-driven automaton technology utilizes causal AI to intelligently power workflows in all multicloud environments.

3. Accenture

Accenture is a global IT service company that provides AIOps as a core capability within its offerings through consulting, implementation, and managed services.

Key AIOps Services of Accenture

• Through their AI-powered automation platform, myWizard, they are transforming IT operations into a predictive and business-aligned function, maximizing efficiency and cost optimization.
• Mainly, they use AI-driven insights for automating repetitive tasks to empower IT professionals to focus more on complex problem-solving.
• They also provide consulting expertise services with a proprietary platform and provide end-to-end transformation.

4. Datadog

Datadog is an AIOps company that embeds AIOps capabilities through a unified observability platform using ML.

Key AIOps Services of Datadog

• Datadog’s core machine learning engine for AIOps is called Watchdog. This automatically analyzes data and detects unusual behaviour without any manual setup. It also includes log Anomaly detection, which baselines log activity and finds deviations.
• Datadog enables end-to-end remediation workflows triggered by alerts, which use pre-built templates to simplify setting up responses.
• They can also predict future resource consumption and apply AIOps principles to the software delivery pipelines.

5. ScienceLogic

ScienceLogic provides AIOps services through the SL1 platform. They provide AIOps services, which are mostly designed to automate and simplify IT operations in complex, hybrid IT environments.

Key AIOps Services of ScienceLogic

• ScienceLogic’s SL1 platform is designed to collect data from a vast range of sources and environments. It automatically discovers and maps all the components in your IT environment and understands the relationship between them. This real-time mapping is the foundation for AIOps 
• One part of ScienceLogic services is that they analyze the context of an incident, including the topology of affected services and historical data. This drastically reduces the Mean Time to Resolution (MTTR).

6. Moogsoft

Moogsoft is a pioneer in providing the AIOps space by focusing on providing a platform for AIOps observability.

Key AIOps Services of Moogsoft

• Moogsoft’s platform is built to reduce noise, detect incidents earlier, automate response workflows, and accelerate root cause and remediation.
• Moogsoft provides tools to create automated workflows that can make a single, enriched ticket in a service management system and notify the teams via Slack or PagerDuty.
• They apply AIOps algorithms to data from any part of the IT stack, like applications, networks, or infrastructure, and give a unified approach to incident management.

7. Deloitte

Deloitte offers an AIOps service through the AIOPS.D platform. Their service aims to automate and optimize processes, improve data accuracy, and reduce manual interventions across different industries.

Key AIOps Services of Deloitte

• Deloitte’s main core services include AIOps consulting and strategy. They evaluate an organization’s current IT operations, identifying pain points and assessing its readiness for AIOps adoption.
• Deloitte’s platform is a plug-and-play modular platform designed to enable autonomous business processes. It uses AI to automate business processes, provide real-time insights, and augment existing systems.

8. IBM

IBM provides a suite of AIOps services through its IBM Cloud Pak for AIOps platform. Their integrated services aim to improve incident management, reduce mean time to resolution (MTTR), and optimize overall IT performance.

Key AIOps Services of IBM

• Through their platform, they use AI to automatically group events from a wide range of monitoring tools, tickets, and logs. It identifies underlying root causes and reduces alert fatigue for IT teams.
• They use ML to detect anomalies and predict potential failures before they impact users. IBM AIOps integrates with its observability portfolio. They do performance optimization through their Application Resource Management (ARM) tool.

9. Price Waterhouse Coopers (PwC)

PwC provides AIOps services through consulting and managed services. Their service focuses on strategy, implementation, and ongoing management, utilizing both proprietary solutions and a broad ecosystem of partner technologies.

Key AIOps Services of PwC

• PwC provides consulting and Strategy services, like checking their readiness for AIOps by evaluating their IT and operational environment.
• They also offer managed AIOps services to monitor IT environments and predict potential issues before they break out. Their service uses machine learning to correlate events and reduce noise. They will improve Mean Time to Resolution (MTTR).

10. EY

Ernst & Young (EY) offers a comprehensive suite of AIOps services to organize business processes and drive digital transformation.

Key AIOps Services of EY

• EY’s AI-enabled automation services aim to boost productivity and reduce manual processes. They support enterprise transformation through intelligent automation through their unified AI platform EY AI, and they connect AI capabilities to drive AI-enabled business transformations. 
• They also offer consulting services to implement automation, process, and service improvement. They also take care of ethically responsible AI use.

Main Services Offered by AIOps Companies

AIOps services are designed to change how IT operations are managed and can be automated to become proactive and intelligent systems. The core services focus on improving uptime, reducing manual intervention, and enhancing the agility of IT infrastructure. The main services offered by AIOps companies are

• Intelligent monitoring and Observability: AIOps aggregates and normalizes logs, metrics, events, and traces from various tools and combines them into a unified platform. This will give a clear picture of data silos and a view of the entire IT environment.
• Event correlation and noise reduction: AIOps platforms use machine learning to identify relationships between alerts and events from disparate tools, and sense the flood of alerts. They automatically group them into an actionable incident. Using algorithms, they suppress non-critical alerts and allow teams to focus on more critical issues.
• Automated root cause analysis (RCA) and incident routing: AIOps methodology uses AI to detect the root cause of the issue by analyzing the correlated events and historical data. This step will save time and accelerate the mean time to resolution (MTTR). AIOps routes the incidents automatically to technical teams with information and actions to be taken.
• Anomaly Detection and Predictive Analytics: This service clearly differentiates itself from traditional monitoring. AIOps companies configure AI and machine learning models to establish a baseline of normal system behaviour. Using AIOPs platforms, they can correlate alerts, detect anomalies, and reduce alert fatigue by using historical trends and real-time data analysis. This predictive Analytics helps IT teams to focus on critical incidents and give warnings about their potential disruptions.
• Performance Monitoring and Optimization: AIOPs companies provide continuous monitoring of applications, infrastructure, and networks as their core service. They help to optimize performance, ensure service availability, and provide predictive insights for capacity planning.
• Consulting and Strategy: AIOPs companies provide strategic consulting, assessing the maturity of an organization’s IT operations. This will ensure that the businesses will select the right AIOps platform, tools, and approach aligned with their needs.

How to Choose the Right AIOps Company for Your Business

With more platform providers and service providers in the market, choosing the right AIOps company is a strategic decision that can significantly impact the IT operations. The factors that influence substantial growth are

• Define your needs: Before selecting an AIOps company, clearly define your goals for what the AIOps solutions will achieve for your business, such as reducing downtime, improving customer experience, automating routine tasks, decreasing alert noise and alert fatigue for your IT, or reducing incident-related downtime and Mean Time to Resolution (MTTR), or detecting any cyber attacks.
• Evaluate the core capabilities of the AIOps company: The best AIOps company should offer a wide range of AIOps solutions. The company should be able to ingest and consolidate data from diverse sources, including logs, metrics, traces, events, and performance data, and perform effective noise reduction and alert correlation to reduce alert fatigue. Look for an AIOps company that uses advanced AI and ML for accurate anomaly detection, root cause analysis, and predictive insights. The AIOPs company can also automate fixes for common, recurring issues, such as restarting a service or scaling up resources.
• Technology and integration capabilities: Ensure that the company seamlessly integrates with your existing monitoring tools, cloud services, and ITSM systems. They should be able to handle increasing volume and variety of IT data as your business grows. Make sure that they adhere to the organization’s security standards and comply with relevant regulations such as GDPR and HIPAA.
• Client review and future-readiness: Gather a proven track record of their successful deployment of a project similar to yours. Ask for case studies, testimonials, and customer references. 
• Cost and Pricing: Cost is a key factor in selecting an AIOps company. Look for an AIOps company that gives a clear and transparent pricing structure, not just on cost but also on ROI. Evaluate all associated costs, including initial licensing or subscription fees, implementation, integration, customization, and ongoing maintenance. Carefully check for any hidden charges mentioned in the pricing structure.
• Ongoing support: Check for the AIOps company’s availability post-implementation. Assess the company’s customer service, training programs, and managed services.

Future Trends in AIOps

AIOps transforms how we manage complex, distributed systems. The following trends reshape the future of AIOps.

• Beyond Anomaly detection: New trends in AI and machine learning will lead to more accurate predictive capabilities. With the improvements in AI models, they will not only identify issues but also predict them before they occur. This will minimize outages and improve service availability.
• Hyperautomation and autonomous IT: The Future will move towards more hyperautomation, where they can not only detect and diagnose issues but also autonomously resolve them. It can manage the entire incident lifecycle from detection to diagnosis, resolution, and even verification. 
• Edge AIOps: Integration of AIOps and Edge computing will become more prevalent, especially for managing data and applications in distributed systems and remote locations.
• Enhanced security: AIOps will play a crucial role in AI-driven security. It will improve threat detection, automated responses to cyberattacks, and overall cybersecurity postures.
• AI-driven observability: Future AIOps will not just process this data but apply advanced AI to provide deep contextual awareness. This means understanding the intricate relationships between applications and infrastructure, and even external factors.
• Deeper Integration with DevOps and MLOps: With the integration with DevOps and MLOps, AIOps helps teams to identify performance gaps earlier, speed up release cycles, and maintain reliability in production environments.

Why Choose Entrans as Your AIOps Partner?

AIOps makes IT operations smarter, faster, and more proactive. With the right AIOps company like Entrans, we can prevent outages, optimize performance, and improve operational efficiency. 

Entrans brings in the integration skills with skilled developers who have more platform knowledge to implement effective AIOps solutions. We help to minimize downtime, enhance performance, and ensure long-term success.

Ready to unlock the full potential of IT operations? Book a consultation call with us.

Frequently Asked Questions (FAQs):

1. What is AIOps, and how does it differ from traditional IT operations?

AIOps, or Artificial Intelligence for IT operations, uses AI/ML to automate, enhance IT monitoring, and remediation. It differs from traditional IT operations by giving real-time insights, reducing alert noise, and enabling faster root cause analysis.

2. What are the key benefits of implementing AIOps in my organization?

The key benefits of implementing AIOps include faster incident response, reduction in Mean Time to Resolution (MTTR), automating repetitive IT tasks, and system reliability. AIOps also reduces alert fatigue by correlating and prioritizing alerts, and it enhances security by detecting unusual patterns. 

3. Which industries can benefit the most from AIOps solutions?

AIOps solutions benefit industries that are complex, data-rich IT environments, customer experience, and have a high need for uptime and efficiency. Mostly banking, e-commerce, healthcare, telecom, and manufacturing industries benefit the most.

4. What are some real-world use cases of AIOps in enterprises?

AIOps is used for intelligent alerting, noise reduction, predictive maintenance, automated root cause analysis, anomaly detection, capacity planning, and proactive monitoring.

5. How do I choose the right AIOps company for my business needs?

To choose the right AIOps company, first define your specific business goals and pain points, then analyze technology capabilities, integration support, scalability, and industry experience. Consider the client reviews, testimonials, and pricing models before making a decision.