Air Space Intelligence Tech Stack
Real-time flight trajectory monitoring and prediction for airspace operations
Air Space Intelligence builds simulation and real-time monitoring systems for airspace and critical infrastructure operations. The tech stack reveals a data-intensive, visualization-first platform: Rust + Python for compute, React + WebGL + Mapbox for geospatial UI, and TensorFlow + PyTorch for trajectory prediction. Engineering-heavy hiring (22 of 26 open roles) paired with active projects around flight diversion detection, turbulence alerting, and dashboard infrastructure signals a company scaling operational fidelity while pushing toward 10x throughput — the architecture choice of Kubernetes + PostgreSQL + Google Dataflow suggests they're optimizing for real-time ingest and sub-second query latency.
Tech Stack 40 technologies
What Air Space Intelligence Is Building
◆Challenges
- Improving airspace safety
- Delivery success
- Scaling infrastructure for 10x load
- Expanding footprint in defense
- Monitoring flight trajectories for large-scale air traffic
- Scaling database usage
- Preventing outages
- Compressing days of analysis into seconds
- Reducing analysis time
- Streamlining operational needs
▲Active Projects
- Flight trajectory monitoring and prediction system
- Detecting when planes are diverted
- Alerting when a scheduled route is expected to hit turbulence
- Scaling infrastructure for 10x load
- Building dashboards for critical alerts
- End-to-end growth strategies
- Building relationships with government agencies
- Real-time flight trajectory monitoring platform
- Mission-critical flight trajectory monitoring ui
- Real-time geospatial decision-making web app
