Inside Ensono’s AI story: Delivering better outcomes for our clients and associates

Quick summary: Ensono uses AI to predict and prevent IT failures, reducing downtime by 62% and major incidents by 22%. Tools like Ensono Predictive Engine and EnsoAI help us optimize client operations and accelerate innovation.

At Ensono, we’re always looking for new ways to deliver better outcomes for our clients. We also want to enhance the experience of working with—and for—us. To this end, we’ve made significant investments in developing our machine learning (ML) and AI capabilities.

It’s been a fascinating journey so far, and the results have been significant. Read on to learn more about how we’re:

• Predicting and fixing major incidents before they occur.
• Accelerating mean time to resolution.
• Enhancing our root cause analysis capabilities to improve operations.
• Deepening our employees’ understanding of client business needs and priorities.
• Helping clients identify their most valuable ML and AI use cases—and getting them into production.

Predicting and fixing IT failures before they occur

As a relentless ally, we’re always looking for ways to help our clients succeed. Supporting hundreds of customers and millions of devices, applications, and infrastructure components, we aim to provide the highest levels of support quality while minimizing downtime and business-impacting events. As a result, our clients have come to expect the highest levels of uptime and superior platform availability from Ensono.

However, as IT systems evolve and complexity rises, achieving our targeted uptime and availability becomes increasingly daunting. Detecting any risk to this—and mitigating it before it impacts our clients’ business—is paramount to Ensono’s continued success.

AI and ML offer the perfect solution: the ability to learn from previous incidents and enable early identification and resolution of issues before they escalate into major incidents.

“Our aim was to move from the ‘monitor, react, repair’ approach followed by most MSPs, to a ‘predict, prevent, optimize’ approach that would be much more valuable to our clients.”

— Jim Piazza, VP, Machine Learning & Predictive Systems, Ensono

Ensono Predictive Engine (EPE)

Ensono Predictive Engineutilizes ML to predict failures using predictive analytics. It unifies and analyzes event logs, performance metrics, and utilization statistics across hardware, operating systems, applications, and networks to identify common precursors to failures. Once found, an alert is sent to the operations team managing that environment, so they can take corrective action before the predicted failure occurs.

Key features and functions of EPE include:

• Proactive monitoring: Continuously analyzes data from various IT systems to detect anomalies and early warning signs of potential problems.
• Incident prediction: Uses ML models to forecast incidents, allowing IT teams to take preventive action and reduce unplanned downtime.
• Automated remediation: In some cases, the engine can trigger automated responses or recommend specific actions to resolve issues before they escalate.
• Operational insights: Provides actionable insights and recommendations to optimize performance, availability, and reliability across hybrid IT environments.

DiagnoseNow

The data gathered by EPE—including previously successful resolution actions—is made available via DiagnoseNow—our second predictive service capability.

This tool minimizes resolution time by using ServiceNow incident numbers to help our teams identify, understand, and resolve issues in a fraction of the time it would usually take. It provides a holistic view of what’s happening across a client’s systems on a single pane of glass. This enables the team to spend less time trying to understand the problem, and more time solving it.

These two systems have significantly enhanced Ensono’s level of service to clients. The ability to identify and resolve issues before they occur has led to:

• 54% reduction in incident mean time to recovery.
• 22% reduction in major incidents.
• 50 major incidents prevented in the last six months.
• 38% reduction in service level agreement payments year-on-year.
• 1,700+ issues highlighted in the last six months.

Minimizing client downtime and enhancing our service levels

By leveraging generative AI in developing root causes analyses, we’re able to quickly identify the underlying reasons for recurring and critical incidents in client environments. This enables us to:

• Minimize client downtime by preventing repeat incidents.
• Improve the quality of our service.
• Demonstrate our commitment to accountability and transparency.
• Enhance our internal processes and team performance.

Deepening our associates’ understanding of client business needs and priorities

Another of our key initiatives has been developing EnsoAI, a friendly assistant that provides robust and secure general-purpose AI capabilities for all Ensono associates. EnsoAI is highly knowledgeable about our business and go-to-market strategies, making it an invaluable tool for our sales, bid, and marketing teams.

The tool helps associates easily search, find, and summarize our collateral and competitive insights. It also enables us to produce higher-quality RFP responses, proposals, and SOWs and makes winning content available to all our teams.

Helping clients identify their most valuable ML and AI use cases—and getting them into production

AI has already had a transformative effect on our business, and the same is true for many of the clients we support—many of whom are already unlocking new opportunities for innovation and efficiency.

It starts with our Innovation Lab Accelerator, a hands-on engagement designed to rapidly prototype and validate AI use cases, de-risking AI adoption, and accelerating time to value.

The Lab uses the Azure Gen AI framework to rapidly deploy proof of concepts and startup projects. This framework supports prompt engineering, fine-tuning language models, and integrates with APIs, file storage, and databases. It’s designed to be extensible, allowing for the swapping of language models and embedding of AI capabilities seamlessly into business processes.

You can explore some of our recent successes by clicking through to the following case studies:

• AI-driven reporting that has transformed data visibility for a leading rail operator.
• A rapid research and probability tool that has enabled better investment decisions for a venture capital firm.
• Unlocking vital engine data and flight patterns to extend engine lifespan, enable predictive maintenance, and deliver huge savings.

What could AI unlock for your business?

For more information on how we’re helping our clients unlock the full potential of AI, visit our website or contact us directly.

Get it touch

FAQ: How Ensono uses AI to improve IT operations

How does Ensono use AI to prevent IT failures?

Ensono uses its Predictive Engine (EPE) to analyze system data and detect early warning signs of potential failures. This allows IT teams to take action before issues escalate, reducing downtime and improving service reliability.

What is the Ensono Predictive Engine (EPE)?

EPE is a machine learning-powered platform that predicts IT incidents by analyzing logs, performance metrics, and system behavior. It enables proactive monitoring, automated remediation, and operational insights.

What results has Ensono achieved with AI?

Ensono has seen a 54% reduction in mean time to recovery, a 22% drop in major incidents, and over 50 major incidents prevented in six months using AI-driven tools.

How does DiagnoseNow support faster issue resolution?

DiagnoseNow leverages historical incident data and AI to help teams quickly identify and resolve issues. It integrates with ServiceNow and provides a unified view of system health.

What is EnsoAI and how does it help IT leaders?

EnsoAI is an internal AI assistant that helps Ensono associates access business insights, generate proposals, and improve client engagement. It enhances productivity and decision-making across teams.

How can clients explore AI use cases with Ensono?

Through Ensono’s Innovation Lab Accelerator, clients can rapidly prototype and validate AI use cases using Azure Gen AI. This helps de-risk adoption and accelerate time to value.