Crest addressed these issues by deploying an AI/ML-driven CMDB solution that connected terabytes of data from various sources, including hardware inventories, network traffic, and more. The system used Deep Learning-powered Natural Language Processing (NLP) for auto-discovery of assets and Graph-based Machine Learning to understand intricate relationships and key bottlenecks. Through predictive analytics and anomaly detection using Random Forest, ARIMA, and other models, Crest allowed the IT team to proactively manage issues, reducing outages and eliminating human error. As a result, this evolution delivered real-time visibility and accuracy, simplified change management, and enhanced IT service delivery.

About the Customer

The customer is a German multinational luxury car company known for its heritage of engineering, innovation, and design quality. It has a significant global footprint, offering a wide range of products from sporty sedans to electric vehicles. Focusing on advanced technology, safety, and environmental responsibility, the company is continually adapting its production and digital operations to provide contemporary mobility solutions while upholding high quality.

Customer Challenge

The customer, a well-known German automotive manufacturer, managed a large and complex IT landscape. The main issue was the difficulty in keeping a Configuration Management Database (CMDB) current. The company heavily relied on manual data input, which was error-prone and unable to keep up with the rapid changes in configuration data within the infrastructure.

This manual approach led to visibility deficiencies, with assets, relationships, and interdependencies between applications and services not being properly tracked. Moreover, the IT staff was spending an inordinate amount of time gathering and validating data, taking away time from more meaningful activities. The lack of an accurate picture of their IT infrastructure negatively impacted their ability to manage change, maintain service, and compliance.

Customer Solution

To tackle the challenges of the client’s IT landscape, Crest deployed an AI/ML-led CMDB solution to consolidate information and automate the asset management process. This solution primarily involved aggregating terabytes of data from various sources, such as hardware and software inventory data, network traffic, monitoring tools, and user logs, into a centralised database. This data was complemented with maintenance logs, software version upgrade histories, and usage patterns to gain deeper insights into the infrastructure.

To achieve accuracy and proactive management, the solution adopted several cutting-edge technologies:

• Machine Learning-Based Discovery and Classification: Crest applied Deep Learning-based Natural Language Processing (NLP) to automatically discover new assets and detect data patterns for classification. Further, unsupervised learning-based clustering was used to cluster assets based on common characteristics and usage patterns.
• Smart Dependency Mapping: To map complex dependencies in the environment, Graph-based Machine Learning models (like PageRank and community detection) were used. This enabled the client to pinpoint key nodes, bottlenecks, and the impact of configuration changes on applications and services.
• Anomaly Detection and Predictive Analysis: The architecture included Time Series Analysis (ARIMA) techniques to identify anomalies in configuration changes based on historical patterns, thereby generating alerts for suspicious changes. Additionally, regression models (such as Random Forest and Gradient Boosting) were applied to historical workload data to forecast potential problems, allowing the IT team to transition from reactive to proactive management.

Outcomes

The AI/ML-enhanced CMDB solution delivered several positive outcomes:

• Automation reduced manual data entry errors, ensuring the CMDB remained accurate and up-to-date in real time.
• The system automatically identified and tracked configuration changes, streamlining the change management process.
• Predictive insights allowed the IT team to take preemptive actions, reducing incidents and minimizing downtime.
• Dependency mapping and usage insights enabled better allocation of resources, enhancing performance and cost-effectiveness.
• Automation and AI-driven discovery saved significant time that was previously spent on manual data collection and validation.
• Accurate and auditable CMDB data supported compliance efforts by providing a reliable record of the IT environment.

About Crest Data

Crest Data is a forward-looking technology partner focused on transforming enterprise IT operations through intelligent automation and data-driven insights. We deliver advanced solutions across AIOps, CMDB intelligence, predictive IT operations, and AI-driven ITSM to help organizations improve service reliability, optimize performance, and reduce operational overhead. By combining deep domain expertise with modern AI capabilities, Crest Data enables proactive decision-making, faster incident resolution, and scalable IT environments aligned with evolving business needs.