AI operations

Keep your AI models cloud infrastructure reliably and cost-effectively

You deployed an AI model. It works today. But AI systems degrade over time. The data changes. Real-world edge cases appear. Model accuracy drifts without you knowing. AIOps is about monitoring what your model actually does, catching performance degradation before it affects decisions, automating the responses to problems, and maintaining reliability without someone babysitting the system. It’s the difference between an AI project that works and an AI system your business depends on.
AIOps
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Where AI Models Break Without Anyone Noticing

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The model was accurate at deployment. Three months later it drifted – and nobody knew until users complained.
01
AI models go live without monitoring. Nobody checks whether they’re still accurate or when performance degrades.
02
When something breaks, you’re debugging after the fact instead of catching it before it happens.
03
Your team is manually reviewing model outputs instead of having the system flag problems automatically.
04
Retraining happens on a schedule or not at all – not when the model actually needs it.
05

Where Are You Starting From?

Just deployed a model – need monitoring before problems happen
Model Monitoring Setup
Model is in production but nobody is watching whether it’s still accurate
Production Monitoring
Managing multiple models manually – need a system that watches all of them
Multi-Model Observability
Model performance has degraded and need to understand why
Drift Investigation
Concerned about edge cases or fairness issues on specific segments
Fairness & Edge Case Monitoring
Need an automated signal for when the model should be retrained
Retraining Automation
Already have AI pilots — need help getting them to production
Pilot-to-Production Roadmap
Pre-IPO or pre-acquisition — need to show AI maturity to diligence
AI Maturity Uplift for Diligence
What can I help with ?

    What Changes

    Five outcomes of proper AIOps.

    You know immediately when your model stops performing

    Not weeks later when someone notices the business impact. Not through customer complaints. The monitoring system tells you the moment accuracy drops or drift increases.

    You understand why the model is degrading

    Is the input data changing? Did a data pipeline break upstream? Are you seeing new patterns in the data? Is the model underfitting new scenarios? You have visibility into what's happening, not just that something is wrong.

    Your team responds automatically to common problems

    A model starts drifting? The system logs it. A specific customer segment is being misclassified? Alerts fire. Data quality drops? You know before the model sees bad data. Some responses are automatic; some require a human to investigate.

    You can retrain confidently and safely

    You know when the model needs retraining because the monitoring tells you. You have historical performance data so you know whether the new model is actually better. You can deploy with confidence.

    Your AI system earns trust over time

    It works consistently. When something does go wrong, your team fixes it quickly because they caught it early. Leadership trusts the model's decisions because it's been reliable.

    How We Engage

    1

    Define what success looks like
    We understand what your AI model does and what “good performance” looks like. What’s the actual business outcome you care about? Accuracy? Precision? Customer satisfaction? Cost savings? We define what success metrics mean in your business context, not just statistical metrics.

    2

    Instrument your model
    We set up logging on predictions, inputs, outcomes, and performance metrics. We create baselines so we know what normal looks like and can detect when things drift.

    3

    Build automated monitoring and alerting
    We identify which problems require automatic responses (retrain, fallback, alert a human) and which need investigation. We create dashboards so your team can see model health at a glance. We establish processes for investigating issues and deciding when to retrain.

    An AI model in production without monitoringis a ticking time bomb

    Start by understanding what your model actually does and how it’s performing. Book an AI operations review. We’ll show you what you’re monitoring, what you’re missing, and how to set up reliable monitoring that catches problems early.
    Round Shape

    Patterns & Platforms

    Model Monitoring Platforms
    Monitoring & Observability
    Data Quality & Drift Detection
    Model Registry & Versioning
    Retraining Orchestration
    Logging & Analytics

    What Clients Say About Working With Exillar

    Excellent work as always by Umair and team. Umair and team continue to provide excellent work product. Highly recommend, responsive and attention to detail. Umair + Exillar team continue to impress and innovate as business needs evolve

    D&K

    D&K | United States

    Thanks for the project. If you are an Executive, you need a PowerBI dashboard. Great working with the team. Many ongoing projects with Umair. Great person to work with.

    Growloup

    Royal Stone | Canada

    These guys are true professionals, they helped me improve the idea of ​​the work I wanted to develop, very kind and prepared. We will definitely do more work together. second work and I’m very statisfied

    willybesmart

    Willybesmart | United States

    The guys were great to work with, very fast to reply and have a deep understanding of PowerBI. This become a learning experience for me as they shared best practices for PowerBI.

    Darcy

    Darcy | United Kingdom

    Thanks for the exceptional work!

    Hans

    Industry MC | United States

    It was a great experience.

    Miguel

    Truespot | United States

    Umair handled my problem timely and efficiently. He is easy to collaborate with and I will be using him again.

    Travis

    United States

    Super good explanation, patience and a good sense of indagatory about the data, sources, etc. The solutions suggested were very safisfactory.

    Raul Rodriguez/F&K

    Chile

    It is always a pleasure to work with Umair and count on his skills to assist us. I highly recommend him. He has excellent communication skills, which makes my life much easier when conveying out needs to a plan, and executing it.

    Alex

    Austria

    Honestly, this has been an outstanding experience from start to finish.The team went far beyond my expectations — not only did they understand a very complex real-world operation, but they were also able to translate it into a functional and well-structured system.

    Latamsa

    Folding Production Control System | Mexico

    Working with Exillar has been amazing. Bhavisha has has gone above and beyond to get us what we need. Very pleased. ~Sherwin

    Loudermilk Homes

    Website development | USA

    It is always a pleasure to work with Umair and his team. Rock start service!

    Alex

    United Kingdom

    Industries We've Worked In

    Retail & E-Commerce
    Healthcare
    Finance & Banking
    Real Estate & Construction
    IoT & Technology
    Manufacturing & Industrial

    Retail & E-Commerce

    Customer analytics, inventory forecasting, and analytics engines that reduce churn and increase basket size.

    Healthcare

    Patient data platforms, clinical reporting, and HIPAA-compliant analytics environments for providers and health-tech.

    Finance & Banking

    Real-time transaction analytics, fraud detection, regulatory reporting, and risk dashboards.

    Real Estate & Construction

    Project data consolidation, budget tracking dashboards, and supply chain analytics across multi-site operations.

    IoT & Technology

    High-volume device data ingestion, stream processing, and analytics platforms for connected product companies.

    Manufacturing & Industrial

    Operational analytics, quality control monitoring, and supply chain visibility platforms.

    Got Questions?

    How do we know what metrics to monitor?
    Start with what matters to your business. For a classification model, is precision more important or recall? For a forecast, do you care about absolute accuracy or directional correctness? For a recommendation system, do you care about engagement or satisfaction? Define that first, then build monitoring around it.
    Critical ones first. If the model drives a business decision or affects customers, monitor it. If it’s an experimental model or low-impact, you can start lighter. We help you prioritize based on business impact.
    When performance degrades beyond acceptable thresholds, or when data distribution shifts significantly. Not on a fixed schedule — on actual performance signals. We set up the triggers that tell you it’s time.
    You can automate most of it — data pipeline, model training, validation. But someone needs to evaluate whether the new model is actually better and decide to deploy it. We automate the mechanics and monitoring; your team focuses on the decisions.