High-volume change logs
Thousands of daily change entries overwhelmed manual review, causing bottlenecks and potential oversights.
Case Study ·
NTT Data
70,000+ Hours Saved
Enhanced Work-Life Quality
Improved Safety & Compliance
About the company
NTT Data is a global digital business and IT services leader, supporting enterprises across industries with scalable technology solutions. Their complex change management operations span massive datasets, with thousands of change logs processed daily. Ensuring operational stability, minimizing risk, and proactively addressing incidents are critical to NTT Data’s mission of delivering uninterrupted service to its enterprise clients. To keep pace with growth and rising customer expectations, NTT Data sought an intelligent solution that could predict incident risks and offer actionable, AI-driven recommendations - all while enhancing team efficiency and decision-making accuracy.
The challenge
The problem statement
Unpredictable incident risk
Without AI-driven analysis, engineers struggled to proactively predict which change logs might trigger incidents.
Manual remediation guidance
Even when risks were flagged, surfacing the right resolution guidelines from historical data was time-consuming and inconsistent.
The approach
How Lyzr solved it
With Lyzr, NTT Data deployed a robust, AI-powered incident management solution - combining machine learning, vector similarity search, and advanced generative models for real-time risk prediction and resolution guidance.
Custom AI Workflow
Change management engineers submit logs via a ReactJS UI. A machine learning model analyzes logs, generating a confidence score on incident risk.
Vector Search for Context
Qdrant powers similarity search across historical incidents, surfacing relevant past cases and resolutions.
AI-Generated Recommendations
A self-deployed GPT-4o-mini model transforms predictions and historical data into actionable incident descriptions and remedial steps.
Enterprise-Grade Security
Okta SAML integration ensures secure, role-based access. Data stored and processed securely via Microsoft Azure Cosmos DB.
Results
The outcome
Faster Incident Risk Detection
AI models proactively assess change logs, cutting down manual risk assessments.
Proactive Remedial Recommendations
Engineers receive AI-generated next steps, improving response times and minimizing incident fallout.
Reduced Manual Workload
Automation frees teams to focus on complex, value-added tasks instead of repetitive log reviews.
Security
How Lyzr handled security
Data Residency
All change management data remains securely within NTT Data’s Azure cloud, ensuring 100% ownership and compliance with regional data laws.
Compliance
The Lyzr Agent Platform is SOC2, GDPR, and ISO 27001 compliant, supporting enterprise-grade data handling and privacy.
Reflection Module
Lyzr’s reflection system minimizes model hallucination, ensuring high-accuracy, reliable recommendations in critical workflows.
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