Integrated Data Intelligence

Poorly optimized data bogs down the business. The opportunity cost of reacting to false alerts and inefficient approaches to real digital environment outages greatly impacts business and financial objectives. A hodgepodge of technical health monitoring tools drives up operational costs due to constant and false alerts. Personnel costs increase and negatively impact other projects when engineering must react to little understood outage incidents.

Leveraging AI/ML against the numerous digital touchpoints allows improved adherence to financial and business objectives. Business-oriented monitoring takes advantage of the existing technology footprint. Mapping the end-to-end user flows, monitors, and objectives builds a leaner, more targeted monitoring capability. The AI/ML engine makes the whole infrastructure more dynamic as it provides real-time anomaly detection and predictive analytics. After deployment, businesses focus on what matters most from a financial and business operations standpoint; guide staff through troubleshooting and resolution for a more targeted, cost-efficient approach; enable self-healing of commonly occurring incidents; and predict the business impact.

pureIntegration offers an agile and flexible partnership engagement in which we implement custom solution tailoring to your specifications. We tackle your organization’s “data pipes” with a view to providing:

• Cost savings and prevention
• Increased Net Promoter Score (NPS) and eNPS
• Effective utilization of team resources
• Revenue improvement (due to more app uptime)
• Reduced false alerts

Service desks represent a critical point of contact for internal and external customers. They can become lengthy and tedious for both the agent as well as the caller, which creates a financial burden: each call represents a cost; the inefficient use of IT resources adds a financial burden, and worst of all eroding satisfaction of customers and employees represents significant financial risk.

The surprising solution? The foundational building block of data management. pureIntegration identifies the issue candidates that would benefit most from AI/ML implementation, and a full review, analysis, and computation of call center data is performed. The predictive engine integrates with your existing ecosystem and the data pipes ensure the right information feeds into the analytics. It includes algorithm development with ML models so that problem/solution codes reach high confidence and accuracy levels. pureIntegration leverages industry-leading practices for a customized ML capability that generates accurate predictions of customer problems and solutions.

pureIntegration’s agile and flexible partnership engagement delivers custom predictive analytics for customer calls solution. At a Fortune 50 company, pI’s AI/ML solution has achieved the following:

• Reduction in average call handling time by over 5 minutes, saving millions of dollars per year
• The problem and the solution for 14% of the most common customer call types with a 99.9% accuracy rate
• Decrease in repeat calling, while increasing overall customer experience and employee satisfaction

Engineering teams who support digital environments face an overwhelming array of tools, but still don’t have the alignment with business or financial objectives. Given the number of tools used to monitor the technical health of the digital environments, constant false alerts generate. Teams waste time responding to the false alert. And, when outages do occur, they have to ramp up staffing and incur headcount costs in order to address the issues. This process riddled with data management issues creates a reactive and inefficient approach to resolution.

The implementation of an AI/ML engine provides these teams with real-time and dynamic anomaly detection. That in addition to the predictive analytics increases their operational efficiency as the engine filters out noise, produces correlations, uncovers causality, enables self-healing, and achieves guided issue troubleshooting and resolution effort. The smart application of these technologies enables the staff to enable business-oriented monitors on top of their current infrastructure. They become more aligned to the enterprise’s needs.

pureIntegration architects a robust data management solution in which we implement a custom engagement tailored to your specifications to provide:

• Reduced false alerts/noise reduction
• Improved Mean Time to Repair (MTTR)
• Enhanced Application Uptime
• Cost savings realized by AI/ML implementation
• Increased Net Promoter Score (NPS) and eNPS

Service desks are inundated with technology and staffing problems that prevent them from efficiently handling calls. They need to provide their organization with the infrastructure to address invalid resolutions to customer issues, improve use of IT resources, and to increase satisfaction levels.

The implementation of a predictive engine acts as a data pipe into your existing ecosystem and increases accuracy around customer problems and solutions. Your engineering team will move the organization to a more proactive stance by analyzing call data and identifying issue candidates that best lend themselves for AI/ML implementation. No new applications would be needed, and instead the focus would be on an environment build-out that includes leading industry best practices. The ML models get developed, trained, and validated so that the problem and solution codes predicated have a high confidence and accuracy level.

pureIntegration implements a data management solution that adjusts to your technical specifications to leverage predictive analytics for customer calls. Our AI/ML solution has achieved the following:

• Addressed the most common customer call type with a 99.9% accuracy rate
• Saved millions of dollars per year by decreasing average call handling time by over 5 minutes
• Reduced repeat calling impact while still realizing increasing overall customer experience and employee satisfaction