How an on-demand delivery platform reduced MTTR by 70% with AI-driven operations

For digital-first companies operating in highly competitive markets, operational stability has become a core business capability. In large on-demand platforms, where millions of transactions happen continuously and customer expectations are measured in seconds, even minor disruptions can have an immediate impact on revenue, brand perception, and partner trust.

This case explores how a leading on-demand delivery platform in Latin America adopted AI-driven IT operations to transform incident management, reduce operational noise, and support always-on performance at massive scale.

The context: Always-on digital operations

The organization operates a large digital marketplace that connects consumers, service providers, and delivery partners across thousands of cities. With tens of millions of monthly transactions, the platform depends on a complex, distributed technology environment that must remain available 24x7.

At this scale, reliability is not just an IT concern, it is a business imperative. Any instability directly affects customer experience, partner operations, and financial performance. 

This reality demanded an operational model capable of detecting issues early, responding rapidly, and sustaining performance under constant demand.

The Challenge: Complexity, Alert Fatigue, and Manual Processes

As the platform expanded, its technology stack and operational footprint became increasingly complex. The existing support model struggled to keep pace, resulting in several critical challenges:

• Extremely high alert volumes across multiple systems and environments
• Significant operational noise, making it difficult to identify incidents that truly required action
• Manual and time-consuming incident investigation and documentation
• Pressure to reduce Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR) without increasing headcount

Traditional monitoring and reactive support approaches were no longer sufficient. The organization needed a smarter, scalable solution grounded in AI-driven IT operations.

-> Read more about: How to measure the value of AI projects from day one

The solution: AI-driven IT operations in a 24x7 Command Center

To address these challenges, the platform partnered with e-Core to design and operate a modern Command Center built around ITIL and ITSM best practices and enhanced by artificial intelligence and automation.

The solution focused on transforming how incidents were detected, analyzed, and resolved.

24x7x365 Command Center Operations
A dedicated Command Center was established to provide continuous monitoring and response, ensuring operational coverage during peak hours, off-hours, and critical business moments.

ITIL-Aligned Level 2 Support
Incident handling and escalation processes were standardized, improving consistency, predictability, and collaboration across teams.

Proactive Monitoring of Critical Environments
Rather than reacting to outages, the Command Center adopted a proactive stance, identifying patterns, trends, and early indicators of potential incidents.

AI-Driven IT Operations Capabilities
Artificial intelligence was applied to reduce manual effort and improve decision-making, including:

• Alert correlation and intelligent noise reduction
  
• Faster and more consistent incident investigation
  
• Automated and standardized incident documentation



By embedding AI into daily operations, teams were able to shift from reactive firefighting to structured, data-driven response.

-> Read more about: Scaling AI Projects: A Framework for Real Impact

The results

The adoption of AI-driven IT operations delivered measurable and sustained improvements:

• Approximately 70% reduction in Mean Time to Resolve (MTTR)
  
  
• Around 57% reduction in Mean Time to Detect (MTTD)
  
  
• Over 90% reduction in Mean Time to Respond
  
  
• Significant decrease in false positives and alert fatigue
  
  
• More stable, predictable operations across the platform

These results translated directly into improved service reliability and operational confidence.

Enabling focus and scalability

Beyond performance metrics, the transformation reshaped how teams worked. With fewer unnecessary alerts and faster, more reliable incident resolution, operational teams experienced reduced cognitive load and lower burnout risk.

Engineers and support professionals could redirect their time toward optimization, innovation, and strategic initiatives.

At the organizational level, AI-driven IT operations became a foundation for sustainable growth, rather than a bottleneck.

-> Want to understand AI better? Read: What AI failures teach us about building smarter systems



Conclusion: AI-driven IT operations as a business enabler

For large digital platforms, reliability and speed are inseparable from business success. 

This case demonstrates how AI-driven IT operations, combined with ITIL-aligned processes and 24x7 Command Center coverage, can dramatically improve incident management outcomes without increasing operational complexity.

As digital businesses continue to scale, investing in intelligent, automated operations is no longer optional. It is a critical enabler of resilience, performance, and long-term competitiveness.

Whether your team is dealing with alert fatigue, slow incident response, or the challenges of scaling always-on operations, the right combination of AI, automation, and ITSM best practices can make a measurable difference. 

Talk to our experts here to explore how intelligent operations can help your teams reduce complexity, improve resilience, and focus on what truly drives business value.