Gigantor Technologies utilizes its patented GigaMAACS technology to enhance the performance of machine learning and AI models by removing hardware limitations, enabling real-time processing of ultra-high definition visuals with near-zero latency. This solution significantly reduces power consumption by 90% compared to traditional GPUs, allowing for larger, more capable models in edge AI applications.
Funding
$2.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
FVFounders
Product
Problem
Edge AI deployments suffer from excessive power consumption, thermal constraints, unpredictable latency, and limited performance, forcing designers to compromise on speed, accuracy, or resolution to meet size, weight, power, and cost (SWaP‑C) limits.
Solution
Gigantor addresses these constraints by converting trained neural networks into custom hardware circuits that execute deterministically on edge devices. This architectural approach delivers supercomputer‑class inference speed with microsecond‑level latency while dramatically reducing power draw and heat generation. The resulting platform supports high‑frame‑rate (240+ FPS) 4K video processing, multi‑target object recognition, and complex sensor fusion without sacrificing accuracy. Gigantor provides an end‑to‑end service: model feasibility analysis, configuration of resolution/FPS requirements, and delivery of a streamlined pipeline and optimized circuit design tailored to the customer’s hardware.
Target Audience
Primary customers are system integrators and OEMs developing edge AI solutions for autonomous drones, robotics, industrial equipment, aerospace & defense platforms, and other real‑time vision or sensor‑fusion applications.
Features
- Automatic transformation of AI models into hardware‑accelerated circuits for deterministic, real‑time execution
- Deterministic microsecond response time with zero jitter, eliminating latency spikes
- High‑throughput video inference capability (240+ FPS at 4K resolution)
- Multi‑target object detection and tracking optimized at the architectural level
- Substantially lower power consumption and thermal output compared to conventional GPU/CPU edge solutions
- Customizable pipeline: customers submit models, define resolution/FPS, receive a hardware‑ready design
- Compatibility with a broad range of edge platforms used in drones, autonomous vehicles, industrial machinery, aerospace, and defense