Building at the edge of the singularity.
Qai Tech holds and builds specialised technology companies at the convergence of quantum thinking, artificial intelligence, and the engineering that turns frontier research into everyday infrastructure.
Three forces, converging on a single point.
Computation at the substrate of reality — the way of thinking that explores spaces classical approaches cannot reach.
Systems that learn, reason, and compound — bending the curve of discovery toward the things we have yet to imagine.
The connective tissue that turns frontier research into infrastructure, and infrastructure into the everyday.
Every system we build bends toward a single point — where intelligence becomes infinite, and all knowledge converges.
Companies we hold and build.
Websites and digital platforms — the group’s digital arm, serving sister companies and external clients.
A smart platform for managing and sharing event photography — built by Qai App.
Civil and defense drone systems — including Shaheen 1, an autonomous AI interceptor. A founding team of nine.
Turning ordinary buildings into integrated, AI-native environments — starting with the home NAS.
Papers & publications.
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Optical Flow Methods for Interceptor Drones: A Critical Review
A critical review of 47 works (2021–2026) on optical-flow motion perception for autonomous counter-UAV interception — spanning classical, CNN (FlowNet, PWC-Net), RAFT, transformer (FlowFormer), edge, and event-camera methods, benchmarked by accuracy, speed, size, and power for SWaP-constrained drones.
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Edge AI and TinyML for Vision Applications in Autonomous Drones: A Systematic Critical Review
A systematic review of Edge AI and TinyML for on-board drone vision across five domains — comparing model compression (quantization, pruning, distillation) and accelerators (Jetson, Coral, Hailo-8, Loihi 2) under the weight, power, and thermal limits of UAV payloads.
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Bridging Strategic Reasoning and Tactical Execution with LLM and RL Agents
A survey synthesizing hierarchical architectures that pair LLM strategic planners with RL tactical controllers. Hybrid systems report ~28% higher task success and better sample efficiency than RL-only baselines on long-horizon autonomous-control tasks.
Approach the horizon with us.
For founders, clients, and operators building toward the singularity — and anyone who wants to work with the group.