TELECOMMUNICATIONS

Gone are the days of customers having to restate their need over and over, being routed from one agent to the next. Now, with deep learning and predictive analytics, service providers can route calls to the correct agent, reducing customers’ average waiting time and providing a seamless experience.

InsightEdge, unifies AI & ML  with transactional processing in a single in-memory real-time analytics platform which powers advanced analytics on massive amounts of data to effectively run deep learning analytics to automatically route calls to agent with the most relevant skills and knowledge.

Even in most cases where fraud is detected, it tends to be too late, resulting in direct revenue loss and additional OPEX. However, by being able to analyze records in real time, service providers can detect call fraud in time, stopping it from impacting costs to customers and avoiding the detrimental impact it can bring to the customer experience.

With streaming CDR analytics and machine learning service providers can identify key performance metrics and be able to search and filter data found in every call detail or call management record.

Streaming analytics of real-time data enriched with historical data,  enables accurate and immediate detection of suspect call activity based on data streams such as switch logins, IP spoofing events, unusual call destinations, and unusual call usage patterns.

InsightEdge can also deliver real-time rating at scale, while persisting aggregated rating information continuously through to the core billing platforms. This way rating processes can be scaled up to optimize the relevant business processes.

IoT introduces huge amounts of data that, when used correctly, can help improve prediction and enable proactive actions to improve every aspect of the business, from operations and customer care to marketing and sales.

As IoT data streams grow and more and more advanced analytics are required for business insight, there is also the need for faster and smarter data ingestion, aggregation, and transformation. InsightEdge unifies real-time AI and ML with transactional processing, in an in-memory platform that  can seamlessly scale with the demands of IoT.

Service providers can leverage the platform at the Edge Cloud, where IoT data  is instantly analyzed and acted upon. The data can also be filtered before it is stored and processed in the data center.

In today’s world of constantly changing customer needs, service providers are seeking to better understand customers, their needs, preferences, and intents. If they don’t provide a relevant and timely customer experience, the competition will gain significant ground.

To fully understand the customer they need to aggregate data from multiple and disparate data sources. And, while they do have access to mounds of customer data, this doesn’t always add up to a unified, 360-degree, accurate view of the customer. With the unification of AI & machine learning with transactional processing in the InsightEdge platform, real-time and historical data, is aggregated and analyzed in the moment, to optimize real-time customer-centric decisions and actions.

The results include hyper-personalized engagements that are finely attuned to the needs of every customer, a more effective care operation with a lower cost to serve, and more successful marketing promotions and campaigns.