Remote Sensing in a Complex World of Service-Oriented Architecture.
Customer intelligence & service assurance platform to reduce turnaround times with quick resolutions that enhance customer experience and satisfaction.
A Production alert for the primary support engineer comes in. He cuts his lunch break short and logs into the system and the production outage bridge. The bridge is less crowded. The customer service representative is taking calls from customers who are not able transact and explaining the situation.
Hours have passed. The production outage bridge has gotten a little more crowded with teams across the ecosystem, including 3rd party integrators and senior management. Customers are still not able to transact. Engineers are analyzing the systems and logs of their respective tier, but the root cause still elusive. Will they resolve the issue? With so many bright minds, yes they will. But the variable is turnaround time. It can vary from a few minutes to several hours depending the complexity of the issue and the underlying invisible layer that triggered it. In the ever competitive nature of business dynamics, customer experience is prime, and any dip in this metric carries the potential of business and revenue loss.
There are two very distinct concerns that stand out from the problem statement. First, the current approaches are mostly reactive in nature. Second, the teams addressing a common issue are working mostly in isolation on their own data sets without end-to-end correlation.
At Prakat, we are focused on solving this industry challenge. Based on our decade of experience with supporting customers in their software integrations and functions, we have come up with a holistic solution that addresses the challenge.
The solution creates a logical data fabric from disparate datasets from across the ecosystem including Application, Computing, Orchestration, Storage, and Network Layers. This system derives actionable data, quality metrics, analytics and insights and creates a “Customer Centric” intelligence engine to power the platform.
Key Components of the Customer Centric Intelligence & Assurance Platform
1. Software Probes
- Listen and mine real-time data
- Ingest data for data streams
- Relay outlier alert data, based on thresholds for the layer
- Index and map data of underlying real-time log data
- Sniffing to monitor system health and alert trigger
- Mine Application, System, Gateway, Network logs for anomalies
- Live Data streams
Scope: Application, Computation, Orchestration, Storage, and Network
2. Core Engine
- Central Enterprise Data Lake for the platform
- Manage and Orchestrate data streams across platform
- Data transformation and aggregation
- Data Intelligence and Data Chaining
- Analytics and Predictive modeling
- ML & AI to enable end-to-end Intelligence and automation
- Actionable data construction and ingestion
- Common Data Bus to integrate data from multiple platforms
- Real-time continuous quality assets enhancement engine
3. 360 Degree View Decision Management Dashboard
- Unified Dashboard for all the systems in the enterprise
- Proactive alerting mechanism and actionable insights
- Roll-up, Slice & Dice, Drill Down data tools
Take away and conclusion:
- Enable data-informed decision making based on the current and future state of the system
- Reduce issue/s of resolution, timelines, and costs
- Enhance quality with real-time data analysis and minimize outages
- Expand customer trust and satisfaction with shorter turnaround times and a stable system
- A robust framework that can integrate with multiple technologies
- Customizable based on architecture of the enterprise