AI Log Analyzer
Turn multi-gigabyte chaos into instant, trusted insights with explainability built in
See AI Log Analyzer in ActionFrom Logs to Intelligence
Modern networks generate enormous volumes of logs across RAN, Core, and Wi-Fi domains — spanning multiple protocol layers such as RRC, NAS, MAC, RLC, and PDCP. Manual log analysis is often slow, error-prone, and reactive, delaying anomaly detection, increasing OPEX, and impacting QoE.
Amantya’s AI Log Analyzer automatically ingests and correlates logs across all network domains, applying advanced ML models to uncover cross-layer dependencies and root causes. It delivers explainable insights through intuitive dashboards, enabling proactive fault detection and faster resolution.
Real-World Outcomes
Faster Issue Resolution
Resolve network faults quickly, ensuring faster recovery and SLA compliance.
Real-Time Anomaly Detection
Get instant AI alerts to minimize downtime and service disruption.
Fewer Escalations
Prevent repeat incidents with proactive insights and quicker response.
Faster Regression Cycles
Accelerate testing and feature rollouts with automated intelligence.
Predictive Outage Prevention
Identify and fix potential failures before they impact customers.
Carrier-Grade Reliability
Deliver consistent uptime and demonstrable SLAs that strengthen trust.
Lower OPEX, Higher QoE
Cut operational costs while improving network performance and user satisfaction.
Actionable AI Insights
Turn raw data into decisions for smarter, self-optimizing operations.
Key Differentiators
Why Amantya’s AI Log Analyzer?
AI at the Core
Every stage powered by ML/LLM models
Unmatched Speed
From multi-gigabyte logs to insights in minutes
Explainability Built-In
Transparent, trusted, non–black-box insights
Seamless Integration
Easy plug-in with bug tracking tools and operator OSS/NMS
Full-Stack Coverage
RF, RAN, mobility, and QoE metrics
Proactive Detection
Flags failures before they impact QoE
Geo + Temporal Views
Maps peak-hour congestion and location-specific issues
Future-Proof Design
Modular and ready for 5G, 6G, O-RAN, NTN
Amantya’s AI Log Analyzer in Action
AI-Powered RCA
Clusters defects and generates session traces in seconds - 80% faster
Cross-Layer Intelligence
Correlates logs across L2/L3 to pinpoint failures
Predictive Insights
Detects anomalies and risk patterns before they impact users
Explainable AI
Provides root-cause context for every anomaly
Insightful Dashboards
Heatmaps, mobility traces, anomaly clusters, and early warnings
AI Toolkit
Isolation Forest, SVM, Clustering, Autoencoder, LSTM, Graph Causal Models
Flexible Integration
Easy plug-in for OSS/NMS and bug tracking systems
Scalable & Future-Proof
Linear scale-out for growing logs and evolving networks
Specialized AI Modules
Each core capability is powered by advanced AI models
Pinpoints abnormal behavior in seconds
- KPI Outliers: Detects accessibility, throughput, and retainability issues.
- Silent Degradations: Flags problems before users notice, preventing downtime.
- Faster RCA: Accelerates root-cause analysis with AI-driven traces.
Uncovers patterns hidden deep in raw logs
- Pattern-Based Alerts: Surfaces recurring issues for proactive remediation.
- Clustered Logs: Groups logs into meaningful patterns using DBSCAN/K-Means.
- Deviation Detection: Autoencoders highlight anomalies from normal sequences.
Understands how one failure triggers another
- Sequential Capture: LSTMs track sequential log behavior across sessions.
- Cross-Layer Links: Graph-based causal inference connects failures across layers.
- Predictive Failures: Identifies cascading issues before they escalate
Translates logs into clear, actionable insights
- NLP Tagging: Tags cells, procedures, and anomalies for easy understanding.
- Trend Summaries: Generates summaries and trend insights operators can act on.
- Decision Support: Highlights actionable insights to guide engineers and testers.
Don’t just see anomalies - understand them
- Why It Happened: Each anomaly is paired with its root cause - from retransmissions and missing responses to RF degradations.
- Drill-Down Clarity: Inspect exact log sequences or KPI deviations that triggered the alert.
- Confidence: Transparent AI insights engineers and operators can act on immediately.