Crest Data worked alongside the customer to design and enhance key features like data ingestion, noise filtration, and machine learning models to resolve these operational bottlenecks. The Crest engineering team was engaged in the entire product release cycle, offering high-quality rollouts and building multiple integrations to ensure that the tool stays up-to-date with changing customer business needs. Furthermore, by extending the automation test suite with engineering assistance for key defects and patches, Crest Data helped the customer enhance product stability and maintain competitiveness in the intelligent monitoring space.

About the Customer

The customer is an AI-driven observability leader that provides intelligent monitoring solutions for smart DevOps. They deliver the most advanced cloud-native, self-service platform for users to instantly see everything, know what’s wrong, and fix things faster. The unique AI-driven resolution functionality ensures faster Mean Time To Acknowledge and Mean Time To Resolution. 

Customer Challenge

The customer is an AI-based observability leader who faced significant operational challenges in spanning its sophisticated ITOps platform for a worldwide customer footprint across telecom, banking, and the finance sector. The major issues faced were:

• Massive Data Complexity: The platform had to ingest and process terabytes of data coming from various third-party sources in a large variety of formats in real-time.
• Signal-to-Noise Ratio: The signal-to-noise ratio posed a significant challenge as we must remove elements of complexity while working to eliminate background noise to derive actionable insight data so DevOps teams can focus on real issues.
• Rapidly Evolving Market Needs: The market is changing quite rapidly, and the customer has to constantly upgrade its core product functionalities and machine learning models to retain its market leader status and presence.
• Third-Party Integration Demands: The customer had to frequently develop and update integrations on its platform to remain compatible with external ecosystems, as its customers used different monitoring, analyzing, and notification tools. 

Customer Solution

Crest Data collaborated with the engineers of the customer to enhance the ongoing support of the company’s AI observability platform.

This solution contains the following key components:

• Core Platform Enhancement: Crest Data played a crucial role in the development of core functionalities associated with data ingestion, noise filtering, and model enhancement.  The aim of the collaboration was also to improve workflow management so that DevOps teams focus on actual issues. 
• Full Product Lifecycle Involvement: The Crest engineering team was involved in every product release stage, enabling high-quality rollouts and consistent product performance.
• Expansive Third-Party Integrations: To ensure the customer remained compatible with the diverse tools used by its customers, Crest Data developed and enhanced numerous integrations for third-party monitoring, analysis, and notification tools. This made the platform an instrumental tool for customers integrating with external ecosystems.
• Advanced Quality Assurance: Beyond development, Crest Data helped build and extend a comprehensive automation test suite to sustain the long-term quality and stability of the product.
• Dedicated Engineering Support: Crest provided on-call engineering support to address high-priority customer issues and patch requests, working alongside the customer’s product support team to ensure rapid investigation and resolution of critical problems.

Outcomes

The collaboration between Crest Data and the customer resulted in several key operational and strategic outcomes that strengthened the customer’s position as a leader in AI-driven observability:

• Retention and Expansion of Customer Base: By rolling out new products and features with a high level of quality, Crest Data helped the customer maintain its loyal customers and attract new ones.

• Sustained Product Quality and Stability: The creation and extension of a comprehensive automation test suite ensured that the platform maintained consistent quality and reliability over time.

• Enhanced Integration Ecosystem: Developing various new integrations transformed the customer to better connect with a wide range of third-party monitoring, analysis, and notification systems.

• Rapid Resolution of Critical Issues: The decision of the customer to implement on-call engineering support enabled them to respond more quickly and effectively to high-priority issues and patches for customers alongside their product support team.

• Continuous Product Evolution: By continuing to add and improve core features, such as noise reduction, data ingestion, and ML models, the platform remained ahead of the curve in meeting the needs of customers and providing actionable insights in complex, large-scale data sets.

About Crest Data

Crest Data is a data and AI-driven technology solutions provider for enterprises and technology innovators across cybersecurity, observability, AIOps, and cloud security, helping them move faster and more securely. We deliver advanced AIOps capabilities, including event correlation, noise reduction, and incident automation, to better streamline IT operations. Backed by strong engineering and AI-driven innovation, Crest Data enables businesses to reduce operational complexity, improve response times, and drive efficient, resilient digital ecosystems at scale.