AIOps Services for Modern IT Operations and Automation
AIOps Services for Hybrid and Multi-Cloud Environment. The AIOps solution offered by Xcelore allows businesses to transform their IT operations that helps in improving visibility, incident management automation, proactive issue identification, and operational resilience.
Experience Built for Enterprise AI Operations
- 3+
- Years of Engineering Expertise
- 50+
- Enterprise Project Delivered
- 175+
- Engineers & Technology Experts
- 15+
- Industry Transformed
Turn IT Complexity Into Intelligence With AIOps
In modern IT environments, metrics, logs, traces, alerts, topologies, deployment activities, and infrastructure signals are always being generated. AIOps helps bring all these signals together so that operations teams can see what’s important and take action accordingly.
Alert overloadIntelligent prioritization
Reduce noise by identifying duplicate, related, and low-value alerts.
Fragmented telemetryUnified operational intelligence
Connect signals across applications, infrastructure, cloud, networks, and services.
Manual investigationAI-assisted analysis
Give teams incident context, dependency relationships, historical patterns, and probable causes.
Reactive operationsPredictive operations
Detect anomalies and emerging risks before they become major incidents.
Repetitive responseGoverned automation
Automate proven remediation workflows with approval controls, safeguards, and auditability.
Limited visibilityService-level context
Connect technical events with service dependencies and business impact.
Runaway observability billCardinality and ingest governance
Manage your telemetry cost by limiting your metrics and keeping older logs in affordable storage and businesses pay for data, really used by the team.
Comprehensive AIOps Services for Modern IT Operations
AIOps Consulting Services
Evaluate your IT operations, determine the gap areas, and develop your AIOps approach to fit into your current technology infrastructure.
- AIOps readiness and maturity assessment
- IT operations and observability strategy
- AIOps use case identification and prioritization
- Monitoring and incident management optimization
- AIOps roadmap and implementation planning
AIOps Implementation & Integration
Integrate AIOps in your current IT infrastructure by adding your monitoring, observability, automation, and incident management systems to streamline processes.
- AIOps platform setup and configuration
- Monitoring and observability tool integration
- ITSM and incident management integration
- Data, event, and telemetry pipeline integration
- Workflow automation and implementation
Unified Observability
Obtain a connected and unified perspective on your complete business operations by aggregating your metrics, logs, traces, events, and services.
- OpenTelemetry-powered telemetry pipelines
- Intelligent metric and log management
- Cross-environment service visibility
- Unified application and infrastructure monitoring
- Service dependency and topology mapping
Intelligent Event Correlation
Prevent alert fatigue by correlating events between applications, infrastructure, deployments, and dependencies to find patterns and connections.
- Intelligent alert correlation and deduplication
- Dynamic anomaly and event detection
- Dependency-aware alert suppression
- Alert storm identification
- CI/CD and infrastructure event correlation
AI-Assisted Root Cause Analysis
Accelerate incident investigation by connecting operational signals with recent changes, service dependencies, performance patterns, and historical incident data.
- Automated root cause identification
- Change and deployment intelligence
- Distributed trace analysis
- Service-level performance analysis
- Dependency-based blast-radius assessment
Predictive Operations and Anomaly Detection
Extend operational intelligence with AI agents that investigate incidents, analyse signals, recommend actions, and execute approved remediation workflows within defined boundaries.
- Predictive capacity and resource forecasting
- Performance and saturation forecasting
- SLO and error-budget monitoring
- Certificate and quota expiry prediction
- Deployment risk assessment
Governed Remediation
Automate repeatable operational responses through controlled playbooks with approval workflows, safety boundaries, rollback mechanisms, and complete execution visibility.
- Version-controlled remediation playbooks
- Approval-based automated actions
- Blast-radius and access controls
- Automated rollback and circuit breakers
- Execution logging and audit trails
Agentic AIOps
Extend operational intelligence with AI agents that investigate incidents, analyze signals, recommend actions, and execute approved remediation workflows within defined boundaries.
- AI-assisted incident investigation
- Role-based agent permissions
- Controlled tool and API access
- Risk-based autonomy levels
- Complete agent action traceability
Find Where AIOps Can Make a Difference for your Business?
Assess your observability, operations, automation maturity, and AI readiness to uncover high-impact opportunities and define a practical roadmap before investing in a full-scale AIOps implementation.
AIOps Capabilities for Industry-Specific Operational Needs
We help in solving industry-specific operational challenges with AIOps capabilities that are built around particular infrastructure, workflows, service requirements, and user priorities.
BFSICatch critical system anomalies, surface priority events fast, and fix issues immediately to keep financial transactions running reliably.
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ISVSMonitor applications and infrastructure, reduce unnecessary alerts, and resolve issues early to keep systems reliable and meet customer SLAs.
FintechSpot problems on high-volume digital platforms and trigger automated fixes so transactions never skip a beat.
RetailSpot slowdowns across storefronts, checkout, and backend operations before they hurt sales or frustrate shoppers.
ManufacturingConnect IT and shop-floor OT data to catch equipment failures early and minimize costly factory downtime.
LogisticsTrack connected systems across orders, warehouses, and shipments to spot disruptions quickly and keep deliveries on schedule.
HealthcarePinpoint and prioritize risks in complex IT setups to keep sensitive, life-critical systems safe and operational.
SaaSLink app and infrastructure events across multi-tenant setups, cut down alert overload, and resolve incidents before customers notice a drop in service.
TravelTie together booking, payment, and fulfillment systems to catch hiccups early and handle massive spikes in demand without going down.
EducationMonitor online learning platforms, catch performance bottlenecks, and resolve incidents fast so students, teachers, and admins have uninterrupted access.
How Could AIOps Transform Your IT Operations?
Build Your AIOps Foundation- Intelligent Infrastructure Monitoring
- Predictive Incident Detection
- Automated Issue Resolution
- Real-Time Operational Insights
- Application Performance Intelligence
- Proactive IT Operations
AIOps Governance and Security for Responsible Automation
All AIOps architectures come with governance as an inherent capability. Role-based approvals, blast radius controls, maintenance mode, dry run capabilities, and risk-based autonomy ensure accountability of automation. By leveraging the power of security in AIOps, Xcelore delivers governance that is compliant with privacy policies of enterprises.
Security
Secure Deployment
Model Access Controls
CI/CD Security
Runtime Monitoring
Drift Detection
Incident Response
Audit Logging
Compliance
ISO/IEC 42001
NIST AI RMF
ISO/IEC 27001
NIST CSF
SOC 2
NIST SSDF
DPDP Act
CCPA/CPRA
PDPL
GDPR
The Technology Ecosystem Behind Our AIOps Services
Python
scikit-learn
Prophet
Dynatrace
Datadog
Splunk
New Relic
ServiceNow
Jira Service Management
PagerDuty
Prometheus
Grafana
OpenTelemetry
Elasticsearch
OpenSearch
Jaeger
AWS
Azure
Google Cloud
Kubernetes
Terraform
Ansible
Jenkins
Python
scikit-learn
Prophet
Dynatrace
Datadog
Splunk
New Relic
ServiceNow
Jira Service Management
PagerDuty
Prometheus
Grafana
OpenTelemetry
Elasticsearch
OpenSearch
Jaeger
AWS
Azure
Google Cloud
Kubernetes
Terraform
Ansible
Jenkins
Ready to Build Smarter IT Operations with AI?
Move beyond reactive monitoring with AIOps engineering that connects observability, intelligent analysis, predictive operations, and governed automation to improve reliability, accelerate resolution, and scale operational intelligence across your enterprise.
A Practical AIOps Implementation Process Xcelore Follows
Our approach will guide you through evaluating your current environment to deploying smart automation and optimizing the system performance.
Evaluate
We assess existing systems, tools, data quality, incident history, and automation maturity to identify quick-win opportunities, address data gaps, and establish a strong foundation for successful smart automation.
Design And Develop
We define the logic of the system including the signals to correlate, root cause analysis, and automation of the standard routine actions. All of it is customized based on your specific policies for operational and security matters.
Deploy
We integrate directly into your existing systems, clouds, and ticketing platforms. Features are deployed gradually, allowing your team to start using smart detection quickly and effectively without any disruption to your processes.
Optimize and Automate
We will continuously optimize the system by monitoring such key metrics as response time, noise reduction, and frequency of the issues. Once the system is proven, we will safely transfer more routine activities to automation workflows.
Let’s talk
Bring Your Ideas to Reality
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Frequently Asked Questions
Can Xcelore manage AIOps on an ongoing basis after go-live?
Yes. Our managed services team can take operational ownership post-implementation, including tuning, expansion, and SLA-backed support.
How can AIOps services improve IT operations?
AIOps solutions can help in reducing the noise of alerts, detect operational problems early on, solve problems faster, and automate routine tasks. This will help IT teams improve reliability in their systems.
What AI and machine learning models does Xcelore use for AIOps?
The choice of AI and machine learning models to be used is dependent upon the use case, data available, and the technological setting. They include but are not limited to anomaly detection, event correlation, forecasting, incident analysis, and automation of operations..
How much do AIOps services cost?
IOps service costs depend on factors such as the size of your IT environment, number of integrations, data sources, monitoring requirements, and level of automation. Xcelore can help define an approach based on your specific requirements.
How do I choose the right AIOps solution for my business?
The right AIOps solution depends on your existing IT infrastructure, operational challenges, data sources, monitoring tools, and automation goals. Xcelore can assess your environment and help define suitable use cases and an implementation roadmap.
Turn Every Operational Signal Into Actionable Intelligence.
Connect observability, intelligent analysis, predictive insights, and governed automation to build more resilient IT operations that reduce noise, accelerate resolution, and improve reliability across your technology environment.