The converged UC and network monitoring platform that eliminates finger-pointing between teams. Per-hop call analytics. SBC health correlation. AI-powered root cause analysis. All on Azure.
When a call drops, UC blames the network. NOC blames the UC stack. Hours of war rooms. Days to root cause.
The result: Two war rooms. Two versions of the truth. Mean time to root cause: 4 to 24 hours. Users calling the helpdesk before anyone knows there is a problem.
NetmonIQ gives UC teams, NOC teams, and executives a single operational view — with the depth each team demands.
"We finally know WHY calls are bad."
"We see voice impact on network decisions."
"One team fixing problems before users notice."
NetmonIQ is not dashboards and charts. The AI layer is what separates it from every legacy monitoring tool on the market.
Powered by Azure AI Anomaly Detector. Learns baselines per-site, per-trunk, per-time-of-day — and alerts when patterns shift, not when thresholds break.
SBC-West jitter increased 40% over baseline in last 15 min. No user complaints yet. Degradation trend detected. Action: Investigate ISP handoff at hop 3. Auto-ticket created (INC0041892).
Powered by Azure OpenAI Service. Correlates CDR data, network metrics, and SBC health into a single causal chain with plain-English narrative.
Call drops on Trunk-3 caused by packet loss at hop 4 (ISP handoff) — coincides with SBC-East CPU spike at 14:32. Resolution: Rebalance sessions across Trunk-2/3.
Powered by Azure Machine Learning. Forecasts SBC capacity, trunk exhaustion, and firmware risk scores before failures occur.
SBC-North will reach 90% session capacity in 14 days at current growth rate. Upgrade firmware v12.3 to v12.5 — 60% fewer SIP 503 errors across the fleet.
Powered by Azure OpenAI Service. Natural language queries across millions of CDRs and network events. Pattern detection matches failures to historical resolutions.
"Show me all calls that dropped last 7 days where root cause was ISP-related." Result: 23 calls, 3 sites. Pattern matches 3 previous incidents — resolved by trunk rebalancing at ISP handoff point.
NetmonIQ runs natively on Azure. Every site monitored, every CDR stored, every AI analysis drives sustained Azure Consumed Revenue.
Real operational impact. Measured before and after deployment.
| Metric | Before | After NetmonIQ |
|---|---|---|
| Mean Time to Resolution | 4-24 hours | 15-30 minutes |
| Monitoring Tools | 2-4 separate platforms | 1 converged pane |
| Team Coordination | War rooms & blame cycles | Shared dashboard & correlated alerts |
| Ticket Creation | Reactive — after user complaints | Proactive — before users notice |
| Firmware Management | Unknown risk exposure | Predictive fleet management |
| Azure Consumption (ACR) | $0/month | $8-60K+/month |
The only platform that converges UC telephony and network operations with Azure AI intelligence.
| Capability | NetmonIQ | PRTG | SolarWinds | ThousandEyes | Native Teams |
|---|---|---|---|---|---|
| UC + Network Converged | ✓ Native | ✗ Network only | ~ Partial | ✗ Network only | ✗ UC only |
| Per-hop Call Analytics | ✓ Full path | ✗ | ~ Limited | ✓ Network path | ~ CQD only |
| SBC Correlation | ✓ Deep | ✗ | ~ Basic | ✗ | ✗ |
| AI Root Cause Analysis | ✓ Azure AI | ✗ | ✗ | ~ Basic | ✗ |
| Predictive Maintenance | ✓ ML-based | ✗ | ~ Thresholds | ✗ | ✗ |
| SNMP Discovery | ✓ | ✓ | ✓ | ✗ | ✗ |
| Azure ACR Generation | ✓ $8-60K+ | ✗ | ✗ | ✗ | ✗ |
| Teams-Native Integration | ✓ Deep | ✗ | ~ | ✓ | ✓ |
They monitor your network. NetmonIQ correlates your network with your voice traffic per-hop. Your NOC sees devices — we show what those devices are doing to your calls.
They show the path. We show what happened to the call ON that path, correlate it with SBC health, and auto-ticket it in ServiceNow with full context.
CQD shows symptoms 24 hours later. NetmonIQ shows SBC and network root cause in real time with AI-generated narrative — before users report the problem.
You have network monitoring AND UC monitoring — separately. That is why it takes days to root cause a bad call. NetmonIQ converges them with AI.
Your Azure subscription. Your data. Your compliance boundary.
Fastest path to production. Enterprise SLAs. Zero infrastructure overhead.
When AI detects an anomaly or a call quality pattern crosses a threshold, an enriched incident is created automatically — complete with per-hop analysis, SBC health data, affected users, and suggested resolution steps.
Anomaly detected: enriched incident created with full diagnostic context
CDR data, per-hop analysis, SBC health, and AI root cause attached to every ticket
SNMP traps correlated with call quality data flow into the incident pipeline
Ticket status changes in ServiceNow reflected in NetmonIQ incident timeline
Historical resolutions surfaced when similar patterns are detected
"Deployed across multi-site enterprises, NetmonIQ eliminates the UC-vs-Network blame game by correlating call quality with network health in a single pane."
— Multi-site enterprise deploymentThree domains: SBC health (CPU, memory, sessions, SIP rates, firmware, CDR correlation), network infrastructure (auto-discovered devices, interface utilization, QoS, SNMP traps), and call paths (per-hop jitter, latency, packet loss). All correlated by Azure AI.
NetmonIQ collects data from both UC infrastructure (SBCs, CDRs) and network infrastructure (SNMP) simultaneously. When a call quality issue occurs, it traces the call path hop-by-hop and overlays network health data from each device along that path.
Azure AI Anomaly Detector for baseline learning, Azure OpenAI Service for plain-English RCA and natural language search, and Azure Machine Learning for predictive models forecasting SBC capacity and firmware risk.
Yes. NetmonIQ augments your existing monitoring stack. It collects from the same SNMP-enabled devices and adds UC + network correlation. Most customers consolidate to NetmonIQ as their primary platform once they see the converged view.
NetmonIQ measures jitter, latency, and packet loss at every hop along the call path — from endpoint through LAN, WAN, ISP handoffs, SBC, and destination. It builds a dynamic visualization showing exactly where quality degraded.
AudioCodes, Ribbon, Oracle (Acme Packet), and Cisco CUBE. Vendor-aware monitoring understands specific health indicators, session counters, and firmware structures of each platform.
Bidirectional. Anomalies auto-create enriched incidents with full diagnostic context. Ticket status syncs back to NetmonIQ. Historical resolutions are surfaced when similar patterns recur.
Two options: BYOC (all infrastructure in your Azure subscription via Terraform) or Fully Managed (EZAIX hosts and operates with enterprise SLAs). Both provide the same platform capabilities.
Every deployment consumes Azure VMs/AKS, SQL/Cosmos DB, AI services, Machine Learning, Monitor, Event Hubs, and Blob Storage. Pilot: $2-5K/mo. Production: $8-20K/mo. At scale: $25-60K+/mo. ACR compounds quarterly.
Yes. Together they form a 360-degree communications operations platform. TeamsCoreIQ handles governance and policy; NetmonIQ handles monitoring, analytics, and AI-driven operations intelligence.
Book a 30-minute technical walkthrough. See per-hop call analytics, AI root cause analysis, and the shared war room in action.
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