MWC26 MAVENIR DEMOS

Design an AI agent by phone, launch it instantly, and watch it run live workflows.

See how businesses can create and deploy AI‑powered voice and messaging agents in minutes, simply by calling or texting. In this demo, a customer uses natural language over voice to design a custom AI assistant for their business, defining appointments, calendar integration, payments, and customer interactions, without writing code. Once created, the agent is immediately activated. Visitors can call in and watch the AI execute workflows in real time: booking appointments, checking availability, and processing transactions through natural conversation. This demo shows how operators move beyond connectivity to become platforms for AI‑driven business automation—turning Voice and Messaging into high‑margin digital services.

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Stop fraud in seconds: ML + sentiment analysis detects and blocks bad calls in real time.

Call Shield detects nuisance and fraudulent calls using machine‑learning models that analyze signaling metadata. Accuracy and speed improve further with AI‑based call‑sentiment analysis. In this demo, the system captures the first 20–30 seconds of a suspect call (for an opt‑in recipient under attack), analyzes sentiment, correlates with ML indicators, and then blocks the fraudster, terminating the call to protect the user and network.

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Instantly classify risky links at mobile scale: AI + messaging intelligence for real‑time protection.

Traditional firewalls and DNS filters rely on email and limited detection points, yet most scams now spread via mobile messaging, and most internet traffic traverses mobile networks. Mavenir Link Shield gets ahead of legacy IP threat intelligence by leveraging mobile‑network visibility, global messaging integrations, and AI‑driven classification to evaluate newly observed domains and URLs in real time. This demo shows how domains/URLs are classified instantly and enriched with enterprise‑grade reporting to protect subscribers and brand trust.

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AI‑powered situational awareness for faster, clearer, smarter NOC operations.

As networks scale, operators require real‑time clarity across increasingly complex infrastructures. This demo showcases how AI‑driven NOC Assistance automatically correlates system metrics and alarms to provide deep, cross‑domain visibility, vertically across infrastructure, platform, and applications, and horizontally across network functions supporting a service. By combining dynamic topology, service‑relationship modelling, and alarm/entity correlation with automated deduplication, the system quickly identifies the most meaningful events. Correlation spans both:- Temporal patterns, events occurring within the same time window across pods and network functions- Spatial patterns, events occurring in the same cluster, NF, or service domain. This comprehensive perspective accelerates problem understanding, reduces noise, and enables faster, more accurate operator decision-making.

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Accelerate MTTR with AI‑driven, always‑adaptive root‑cause intelligence.

This demo showcases how Mavenir’s Auto RCA engine rapidly identifies the true causes behind service degradations, network faults, and performance anomalies. Leveraging AI/ML‑driven correlation and dependency models, the solution analyzes multi‑domain telemetry (spanning IMS Core, PaCo, and OSS/BSS), to trace fault propagation paths and isolate root causes with precision. Operators gain clear, actionable insights through intuitive visualizations that significantly reduce mean time to repair (MTTR) and minimize service disruption. The system continuously adapts to network changes, accounting for shifting topologies and planned maintenance activities .Auto RCA is a key enabler of closed‑loop automation, driving major improvements in operational efficiency while ensuring superior network reliability.

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AI‑driven diagnosis and auto‑remediation for faster, smarter customer care.

Experience how an AI‑powered, multi‑modal agent transforms customer service by instantly diagnosing and resolving technical issues. The system verifies a subscriber’s profile, services, provisioning status, and live network data, detects configuration or delivery gaps, and automatically applies corrective actions across network nodes. Beyond fixing individual cases, the agent identifies patterns across subscriber segments and raises proactive tickets, evolving operations from reactive troubleshooting to predictive care. This reduces L2 workloads, increases first‑call resolution, and enhances overall care efficiency.

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From idea to launch‑ready offer in minutes, powered by conversational AI.

Discover how a conversational AI agent accelerates the creation of new telco offerings. By interpreting product intent, the system generates TMF‑compliant specifications, builds commercial and technical catalog entries, creates fulfilment flows, and validates configurations through automated end‑to‑end testing, making the offer launch‑ready within minutes. This approach eliminates manual catalog work and dependency on IT teams, improves product robustness through automated validation, and frees product managers to focus on market innovation rather than operational tasks.

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