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NDA project
An AI-powered computer vision platform enabling real-time object recognition directly onboard UAVs, improving situational awareness and accelerating mission-critical decision-making.
MilTech
UAV Manufacturer
Web-based + Onboard AI Integration
Dedicated
Development Team
A UAV manufacturer sought to enhance reconnaissance and monitoring missions by augmenting operators with automated visual intelligence. Previously, teams relied on manual interpretation of live drone video streams, creating cognitive overload and delayed reactions in dynamic operational environments.
The client required onboard AI capable of assisting human operators without compromising performance on constrained hardware.
Operational Complexity: continuous manual monitoring of live video streams reduced operator efficiency.
Hardware Constraints: AI models needed to operate reliably on limited onboard computing resources.
Environmental Variability: changing terrains, lighting conditions, and object types impacted recognition accuracy.
Decision Reliability: outputs had to remain interpretable and trustworthy for human validation.
We built a real-time edge AI pipeline optimized for UAV environments. Live video streams are processed directly on UAV hardware, with synchronization to central analytics for mission intelligence.
The system integrates onboard object detection, classification, and pattern clustering, with confidence scoring for human-in-the-loop validation and MLOps pipelines for continuous model improvement.
1x
Computer Vision Engineer
1x
ML Engineer
1x
DevOps Engineer
1x
Data Scientist
2x
Data Engineers
1x
QA Engineer
1x
Project Manager
1x
Computer Vision Engineer
1x
ML Engineer
1x
Data Scientist
2x
Data Engineers
1x
QA Engineer
1x
DevOps Engineer
1x
Project Manager
Real-time video analysis engine
Computer vision recognition models
Edge inference modules
Object clustering algorithms
Mission logging & synchronization system
ML lifecycle pipelines
Full breakdown is available under NDA, on request
Discovery & Planning: 3–4 weeks
Architecture & Design: 4–6 weeks
Development: 4–6 months
Total Timeline: ~6–8 months
Discovery Phase: $25K–$40K
Design & Architecture: $40K–$70K
Development: $180K–$320K
Total Investment: $300K–$450K
Share a few details — we’ll map scope, timeline, and cost
Reduced operator cognitive load and accelerated field response
Stable edge AI inference and scalable ML lifecycle
Improved mission efficiency and decision accuracy
