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Beegol Tech Stack
ML platform for real-time broadband and WiFi quality monitoring
Beegol builds ML-driven network monitoring for telecom operators, detecting service degradation and outages before customers experience them. The tech stack (Python, AWS, Redshift, PostgreSQL) and active project list reveal a company scaling toward AI agents and LLM-based diagnostics — a shift from rule-based detection toward learned pattern recognition. Engineering-heavy headcount (218 of 223 hires) focused on data pipelines and ML training suggests they're shifting from reactive monitoring to predictive, autonomous issue resolution.
Tech Stack 13 technologies
Core StackPython AWS AWS Lambda Terraform GitHub Redshift PostgreSQL SQL API Gateway AWS ECS AWS Fargate MLOps AWS API Gateway
What Beegol Is Building
◆Challenges
- Processing large volumes of data
- Detecting network issues quickly
- Improving network diagnostics accuracy
- Handling large data volumes
- Network issue detection
- Reducing time to detect network issues
- Scaling data pipelines
- Reducing network downtime
- Detecting network problems
- Improving broadband quality
▲Active Projects
- Ai agent architecture integration
- Llm training and fine-tuning for production products
- Data pipeline design and maintenance
- Data pipeline for quality and reproducibility
- Data pipeline for collection, cleaning, transformation, and versioning
- Define ai agent architecture and integrate components into products and apis
- Llm training, fine-tuning, and evaluation pipeline
- Llm training pipeline
- Llm training and evaluation
- Design, build, and maintain data pipelines with focus on quality and reproducibility
Hiring Activity
Minimal250 roles · 1 in 30d
Department
Seniority
Company intelligence
