To add AI building blocks to your demonstrator: perception, tracking, autonomous navigation.
Visual and LiDAR perception systems with AI.
Visual tracking algorithms for moving targets.
Trajectory planning and obstacle avoidance.
AI model deployment on embedded system.
Interface with robotics frameworks.
Each engagement starts with the demonstrator constraints that matter most on demo day: embedded platform, payload interface, communication link, operating scenario, operator workflow, and failure modes. We focus on the last-mile integration work that turns a lab prototype into a field-ready demonstration.
The work can include STM32 or ESP32 firmware review, sensor and actuator integration, UAS payload stabilization, MQTT/Modbus/REST interface checks, telemetry validation, checklist preparation, and repeatability tests. The objective is not to add complexity, but to remove the failure points that would weaken a client, investor, or procurement presentation.
Yes. These offers serve as a decision framework, then the exact support is calibrated to your deadline and maturity level.