Bringing AI computation to the edge of the network — enabling real-time, privacy-preserving intelligence in IoT devices, smart infrastructure, and autonomous systems without dependence on the cloud.
About the Division
The Edge AI Research division at Presear Softwares investigates how intelligence can be embedded directly into the devices, sensors, and systems that generate data — eliminating latency, preserving privacy, and enabling AI to operate in environments where constant cloud connectivity is impractical or impossible.
Our research spans the algorithmic and systems dimensions of edge intelligence: model compression techniques that fit deep neural networks onto microcontrollers with kilobytes of RAM; federated learning protocols that let edge nodes collectively train shared models without centralising raw data; and real-time inference pipelines optimised for battery-constrained or thermally limited hardware.
We deploy and validate our research across diverse real-world contexts — from smart city sensor networks and industrial floor monitoring to precision agriculture and connected medical devices — ensuring our algorithms survive the unpredictability of field conditions, not just benchmark datasets.
Research Focus
Five interconnected areas where Presear's Edge AI Research division is pushing the frontier of distributed, on-device intelligence.
Compressing and optimising deep learning models to run on microcontrollers, embedded processors, and bare-metal hardware — enabling AI inference with milliwatt power budgets and minimal memory footprints.
Designing privacy-preserving distributed learning protocols that allow edge devices to collaboratively improve shared AI models without ever transmitting raw data to a central server — reducing both privacy risk and bandwidth cost.
Advancing quantisation, pruning, neural architecture search, and hardware-aware compilation techniques that maximise inference accuracy and throughput on resource-constrained edge devices across heterogeneous hardware.
Building and deploying AI systems for intelligent urban infrastructure — real-time traffic management, predictive utility monitoring, environmental sensing, and adaptive public services — directly on edge compute nodes.
Developing perception, planning, and control AI for mobile autonomous systems — drones, ground vehicles, and robotic platforms — that must operate with low-latency, high-reliability intelligence entirely on-board.
We partner with device manufacturers, system integrators, and city governments to pilot and scale edge AI deployments from prototype to production infrastructure.
Presear Edge AI Research works with hardware manufacturers, smart city programmes, and industrial operators to deploy AI where the data lives — at the edge, in real time.