Engineering

Engineering & System Validation

Design, simulation, and validation frameworks developed by AID Edge Inc., powering the Velorona decision layer.

Edge-processing hardware representative of the CPU-first, resource-bounded architecture behind AID Edge's inference research.
Resource-bounded, CPU-first — the inference footprint AID Edge designs around.

Ultra-Low Latency for Critical Connectivity

By processing data at the edge, Edge & Hybrid AI drastically reduces latency, enabling telecom networks and satellite systems to deliver secure, real-time communication.

Earlier Fault Detection

Edge intelligence identifies degradation patterns before conventional monitoring reaches escalation thresholds.

Resource-Aware by Design

Architecture designed to operate close to critical network telemetry without requiring infrastructure overhaul.

Engineering Foundation

AEI SDK, libraries, and architecture

The applied systems powering the Velorona decision layer and future products.

01

AEI SDK

AEI-SDK v0.9 — AI libraries designed with traceability and reviewability in mind, for secure, licensing-based integration into existing telecom infrastructure.

02

Reusable Libraries

Modular components shared across AID Edge’s Edge AI and decision-intelligence systems, built once and reused across engineering initiatives.

03

Edge AI Architecture

Resource-bounded, CPU-first inference paths designed to preserve operational stability without requiring infrastructure overhaul.

04

Resource-Aware Systems

Systems that step back under constrained conditions to preserve network forwarding, control, and service continuity.

05

Operational Demonstrations

Simulation-level validation of AID Edge’s decision architectures — the stage where research findings are checked against operational constraints before any production use.

06

Selected Open-Source Releases

AID Edge has developed 22 reusable engineering libraries within the AEI SDK. Selected, non-differentiating components are released publicly as they reach production maturity.

aei-3gpp-kpi-validator

A dependency-light Python validator for real 3GPP-standard telecom KPIs (RSRP, RSRQ, SINR, handover quality, NB-IoT power) — cites the actual TS specs, and states plainly what it does not implement.

aei-geo-features

Small, dependency-light geospatial feature primitives: distance, jitter, coordinate validation and normalization.

These are selected public components from AID Edge’s internal engineering library ecosystem. Velorona’s proprietary decision-intelligence logic is not open-sourced.


Validation Approach

Where this engineering gets validated

Velorona validates this engineering against real recorded telemetry from live microwave radio hardware, not synthetic data — the product this engineering powers, not restated here.

See how this engineering becomes a product