Spectrum Effect offers Spectrum‑NET, a cloud‑native AI platform that automatically detects, classifies, and mitigates RF interference across 5G, LTE, and UMTS networks. By leveraging convolutional neural networks and a single‑pane‑of‑glass dashboard, it provides real‑time interference remediation and root‑cause analysis, enabling mobile operators to improve spectral efficiency, reduce OPEX, and enhance user QoE.
Funding
$2.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Mobile operators experience significant performance degradation due to unchecked RF interference, leading to reduced user throughput, poor voice quality, higher call and handover failures, and diminished coverage. Identifying, classifying, and mitigating this interference manually is time‑consuming, error‑prone, and costly, impacting both CAPEX efficiency and OPEX budgets.
Solution
Spectrum Effect delivers Spectrum‑NET, a cloud‑native AI platform that automatically detects, classifies, and mitigates RF interference across 5G NR, LTE, and UMTS networks. The solution leverages convolutional neural networks trained on millions of labeled interference samples to provide real‑time interference classification and root‑cause analysis. Detected issues are auto‑mitigated through QoE‑driven actions, TDD self‑interference correction, and cross‑border interference handling, all orchestrated via a single‑pane‑of‑glass dashboard. Integration options include REST APIs, SON/RIC rApp deployment, and plug‑ins for existing automation frameworks, enabling seamless incorporation into operator workflows. The platform runs on Kubernetes‑orchestrated microservices, supporting public, private, hybrid clouds or on‑premise data centers, and meets tier‑1 security standards.
Target Audience
Primary customers are mobile network operators and RAN service providers seeking to improve spectral efficiency, reduce interference‑related outages, and automate network optimization across 5G and legacy LTE/UMTS deployments.
Features
- AI‑driven interference detection using convolutional neural networks trained on >300k labeled samples and 7 M+ hours of RF data
- Automatic classification into 16 interference types with patented algorithms
- Real‑time QoE auto‑mitigation, TDD self‑interference correction, and cross‑border interference mitigation
- Single‑pane‑of‑glass dashboard providing network‑wide performance visibility and prioritized remediation
- REST API, SON/RIC rApp, and third‑party system integration for end‑to‑end automation
- Flexible deployment on operator‑owned clouds, dedicated data‑center servers, or Spectrum Effect‑hosted AWS environment
- Kubernetes‑based microservices architecture ensuring horizontal scalability and high availability
- Built‑in security scanning (Twistlock, Nessus, Qualys) to satisfy tier‑1 operator compliance