Telco IT AI Apps

Ericsson Telco IT AI Apps offers a set of cloud native AI applications designed to augment OSS/BSS features and elevate the observability of OSS/BSS systems through various AI use cases. These AI applications are offered as fully managed services to CSPs, leveraging data from Billing, Charging, Catalog Manager, Expert Analytics, CRM, Order Care, Service Orchestration, Network Manager and Mediation to provide customer, service, and operations insights. Ericsson Telco IT AI Apps are available either on Ericsson's MITO.ai platform or on AWS SageMaker. We have capabilities to host these AI Apps on other HCP platforms. 

Telco IT AI Apps includes following three suites of AI-based intelligent insights addressing the distinct business and operational needs of CSPs:

1. Intelligent Customer Insights – Leverage the power of AI to derive actionable insights from data to improve sales, reduce revenue leakage and enhance customer experience. Intelligent customer insights enable CSPs to:

• Unmask billing anomalies: Identify potential errors before they impact your customers and revenue.
• Personalize marketing approach: Tailor offerings and marketing messages based on individual needs and preferences.
• Make smarter decisions: Gain insights from complex data to optimize pricing, marketing, and product development.
• Stop churn before it starts: Uncover hidden customer insights to personalize experiences, predict & prevent churn, and win back lost customers.
• Adapt quickly to changing market conditions: Make intelligent decisions to tailor business configurations to your needs and goals.

2. Intelligent IT Operations – Harness the power of AI to analyse data and gain predictive insights for smooth-running OSS/BSS operations. Intelligent IT operations facilitate:

• Real-time anomaly detection: Continuously monitor OSS/BSS systems using advanced analytics and AI for unusual patterns that might indicate potential issues, ensuring comprehensive end-to-end service monitoring.
• Predictive order success:  Analyse order processing systems data in near-real-time using unsupervised machine learning to predict potential roadblocks and prevent order failures.
• Automated ticketing: Automatically categorize and assign incoming tickets to the appropriate team for faster resolution.
• Resolution recommendations: Recommend actionable fixes for reported issues using deep learning and natural language processing (NLP) to correlate historical ticket data with resolutions for accelerated resolution.

3. Intelligent Service Insights – Utilizes AI to gain network and service insights to proactively identify service degradations and enhance customer experience. Intelligent service insights enable CSPs to:

• Forecast Network Anomalies: Identify network issues before they impact customers and understand the underlying causes for proactive resolution.
• Profile subscribers based on usage: Profile subscribers based on their service usage behaviour and preferences, enabling targeted marketing and sales efforts.
• Analyse network coverage and capacity: Forecast traffic growth and identify congested areas to proactively optimize network capacity and prevent signal dropouts.

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