AI-powered autonomous flight software for extended drone operations
Shearwater Aerospace builds autonomous flight software that uses AI and wind modeling to extend drone endurance and operational capability. The tech stack—Vue, GCP, Cesium.js, PostGIS, GDAL, NetCDF—reflects a geospatial-first architecture designed for real-time flight planning and weather integration. The company is pre-revenue and actively hiring senior engineers and data specialists across Canada, focusing on route optimization, simulation fidelity, and operator trust, suggesting they are scaling technical depth before commercial traction.
Shearwater Aerospace, founded in 2018 and based in Montreal, develops autonomous flight software for unmanned aerial systems. The product combines AI-driven route planning with meteorological data integration to optimize drone flight time and speed. The engineering is concentrated around simulation (flight dynamics, fidelity standards), real-time guidance logic, and geospatial visualization. The company is in early commercial stages, with active pilot deployments and a small, senior-heavy team focused on bridging the gap between simulation validation and real-world autonomous reliability.
Vue, GCP, Cesium.js, TypeScript, Cloud Run, Terraform, PostGIS, GDAL/OGR, and NetCDF. The stack emphasizes geospatial data processing and web-based flight visualization.
Route planning and optimization, real-time flight guidance, weather intelligence integration, flight simulation, 3D geospatial visualization, and CI/CD pipelines. Active pilot deployments are underway.
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