Airespace provides cloud-native infrastructure solutions designed for modern data workloads. The platform offers scalable compute and storage optimized for high-performance applications. This enables organizations to deploy and manage complex data pipelines efficiently across hybrid cloud environments.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises with large, distributed wireless deployments often lack continuous visibility into the radio frequency (RF) spectrum, making it difficult to detect, diagnose, and remediate interference that degrades network performance and reliability.
Solution
Airespace delivers a cloud‑native platform that aggregates real‑time spectrum data from edge sensors across the entire RF footprint. The service applies AI‑driven analytics to automatically identify, classify, and predict sources of interference, enabling operators to address issues before they impact users. Detected events are correlated with network topology and device inventories, and the platform generates actionable remediation recommendations that can be executed via integrated orchestration APIs. Results and trends are visualized in a web‑based dashboard that supports multi‑tenant access, alerting, and export to existing network‑management systems. The solution scales horizontally in the public cloud, ensuring low‑latency processing for thousands of concurrent sensors while maintaining data security and compliance.
Target Audience
Primary customers are telecom operators, large‑scale enterprise IT departments, and industrial IoT providers that manage extensive Wi‑Fi, private LTE/5G, or mixed‑technology wireless networks.
Features
- Continuous spectrum ingestion from heterogeneous RF sensors (Wi‑Fi, LTE, 5G, private‑cell) via MQTT or gRPC streams
- AI‑based anomaly detection and interference classification using deep‑learning models trained on multi‑band datasets
- Predictive interference modeling that forecasts hotspot emergence based on historical patterns and environmental factors
- Automated remediation workflow engine with REST/GraphQL APIs for dynamic channel reallocation, power adjustment, or device configuration
- Cloud‑native microservices architecture deployed on Kubernetes for elastic scaling and high availability
- Interactive dashboard with heat‑maps, time‑series analytics, and drill‑down views linked to network topology maps
- Vendor‑agnostic integration layer that syncs with existing NMS, OSS/BSS, and SIEM platforms via standard protocols (SNMP, NETCONF, Syslog)
- End‑to‑end encryption, role‑based access control, and audit logging to meet enterprise security and compliance requirements