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Eliminating the Cost of Silence

Operational Intelligence for Risk-Aware Telecom Operations

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About AID Edge Inc. (AEI)

What We Deliver for Network Operations

Why Outage Prevention Still Costs Telecom Operators

Product Ecosystem

Our Operating Philosophy

How We Lead

AID Edge Inc. (AEI) is an infrastructure software company focused on reducing operational risk in telecom networks.

We build edge-native operational intelligence that surfaces early instability and “false calm” conditions, long before issues escalate into widespread alarms or service-impacting incidents.

Our systems analyze link behavior and degradation patterns at the operational edge, helping Network Operations teams prioritize risk, reduce noise, and act with confidence, without replacing existing monitoring or alarm platforms.

Today, our focus is on wireless network operations. The same decision logic is designed to extend naturally to satellite-linked and non-terrestrial networks as connectivity architectures evolve.

  • Early Degradation Detection, identifying edge-level risk patterns before service impact.

  • Outage Prevention, decision intelligence designed for proactive mitigation, not post-incident reporting.

  • Operational Decision Support, outputs aligned with SLAs, NOC workflows, and change-control realities.

Unplanned outages remain one of the highest operational cost drivers in telecom networks, driven by SLA penalties, truck rolls, and customer churn.
Legacy systems often alert after impact; operations teams need time before degradation reaches customers.
AID Edge Inc. (AEI) is built to enable earlier detection, local action, and measurable reduction in MTTR and operational risk.

Velorona.ai™ is the flagship deployment of AID Edge Inc.’s edge-native operational intelligence layer.

Positioned ahead of traditional OSS and alarm systems, Velorona detects early instability and silent drift at the link and operational level, before metrics are averaged, thresholds are crossed, or alarms are triggered.

By operating directly at the edge and preserving fine-grained behavioral signals, our layer surfaces emerging risk patterns that legacy monitoring systems inherently miss, enabling earlier, calmer, and more defensible operational decisions.

Insights from distributed edge deployments are selectively fed into a centralized intelligence platform, where models are refined and decision logic is applied across the network, augmenting existing OSS, NMS, and vendor tools rather than replacing them.

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  • Decisions before alarms, not after incidents.

  • Action at the edge, not delayed by centralized workflows.

  • Built for operators, not just dashboards.

We lead from within the system, not above it. Decisions are grounded in operational reality, accountability, and time-to-impact. Our leadership is measured by the clarity we provide to operations teams: If an insight cannot be acted on in the next shift, it does not belong in our production.

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