Beegol is a machine learning platform that provides real-time network diagnostics to monitor and enhance the quality of broadband and Wi-Fi services. It identifies connection issues and optimizes maintenance processes, reducing problem resolution time and improving customer experience for Internet Service Providers.
Funding
$6.4M 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
Internet Service Providers (ISPs) face challenges in maintaining optimal broadband and Wi-Fi service quality, leading to customer dissatisfaction and increased operational costs. Identifying the root cause of network issues, such as connection drops and slow speeds, can be time-consuming and often requires costly on-site visits. Reactive troubleshooting methods also delay problem resolution, impacting customer experience.
Solution
Beegol offers a machine learning platform that provides real-time, end-to-end network diagnostics, enabling ISPs to proactively monitor and enhance the performance of broadband and Wi-Fi services. The platform identifies the root cause of network issues across Wi-Fi, broadband, transport, CDN, and DNS, alerting both ISPs and subscribers to potential problems. By mapping ISP data collections with Beegol's proprietary database and running machine learning algorithms, the platform detects anomalies and provides insights to improve Wi-Fi experience. This allows for optimized maintenance processes, reduces problem resolution time, and minimizes unproductive truck rolls, ultimately improving customer experience and reducing operational costs.
Target Audience
The primary target audience includes Internet Service Providers (ISPs) seeking to improve customer experience, reduce operational costs, and proactively manage their network infrastructure.
Features
- Real-time network monitoring to detect connection drops and their duration.
- Frequent speed test analysis for proactive identification of performance issues.
- AI-driven root cause analysis across the entire end-to-end network.
- Integration with existing ISP systems for seamless data mapping and analysis.
- Machine learning algorithms to identify anomalies and predict potential network issues.
- "Hunter Pack" for comprehensive problem identification across Wi-Fi, broadband, transport, CDN, and DNS.
- "Data Sniffer" for machine learning and database mapping on ISPs' data to improve Wi-Fi experience without agent integration.
- "Mesh Friend" for deploying a fully integrated and cost-effective Wi-Fi mesh solution.