Carlsbad, California, April 25, 2025 – GigaIO, an edge-to-core AI platform, today announced the general availability of Gryf, which the company said is the world’s first suitcase-sized AI supercomputer.
Co-designed by GigaIO and SourceCode, Gryf delivers data center-class computing power to edge operations, enabling real-time intelligence and analytics in previously difficult field conditions. The platform has already secured significant orders from the U.S. Department of Defense and the intelligence community.
GigaIO said Gryf redefines on-demand configurability in the field. Powered by GigaIO’s AI memory fabric, Gryf enables users to dynamically deploy applications anywhere, at any time. The revolutionary computing platform allows organizations to process critical data on-site without latency issues from data transfers, providing unprecedented computing power in a ruggedized, field-ready design that can be deployed virtually anywhere.
“Gryf represents a fundamental shift in how organizations access and utilize high-performance computing at the edge,” said Alan Benjamin, CEO of GigaIO. “By bringing supercomputing capabilities to field operations in a portable form factor, we’re enabling real-time intelligence and analytics that were previously impossible without massive infrastructure. The strong interest from defense, intelligence, sports, media organizations, and the energy sector confirms the market need for this revolutionary approach to edge computing.”
One of Gryf’s most innovative features is its scalability, allowing users to stack up to five units for increased performance while maintaining portability. The units interconnect across GigaIO’s AI fabric, allowing any server to access any resource within the fabric as if it was on a single node. This configuration can be adjusted in real-time to meet changing application requirements.
The system’s customizable design, featuring GPU, compute, storage, and network sleds, enables organizations to optimize configurations for specific workload demands, maximizing return on investment while providing a smaller footprint and lower power draw than traditional solutions.
Designed and built in the US, Gryf has quickly gained traction within defense and intelligence sectors, where its portable data center performance and AI-enhanced capabilities enable mission-critical workloads at the tactical edge. The platform is optimized for AI, Intelligence Surveillance Reconnaissance (ISR), cybersecurity, and tactical missions, providing commanders with immediate insights without requiring data transmission to remote processing centers.
The seamless edge-to-core integration between Gryf and GigaIO’s SuperNODE system enables field units to operate autonomously and then synchronize instantly with central computing resources upon connection. This revolutionary capability ensures continuity of operations across the disconnected, intermittent, and limited bandwidth environments common in defense operations.
Gryf significantly elevates sports analytics at remote training locations, stadiums, race courses, and practice facilities by providing instant data analysis at the edge with its portable AI-powered data center capabilities. The platform’s ability to analyze speed, workload, heart rate, and other performance metrics in real time enables data-driven decisions that optimize performance and prevent injuries, providing coaches and performance staff with immediate insights during training and competition
“Sports teams competing at the highest levels need immediate access to performance insights,” noted Lauren Spurlin, Founder, Aurified Consulting. “Waiting hours or days for data processing is no longer acceptable. Gryf eliminates those delays by bringing the data center directly to the field, changing how teams train, compete, and recover.”
GigaIO said adopters of the Gryf in media and entertainment are seeing improvements in production workflows. Deployed on set, Gryf decreases post-production time for sports broadcasts and entertainment productions by enabling on-site processing of high-resolution content.
Gryf’s high-performance computing and storage capabilities support on-site live broadcasting, rapid content processing and editing, real-time analytics, and enhanced graphics generation. Particularly effective at outdoor venues with challenging high-speed connection points, such as NASCAR race tracks and sports stadiums, Gryf can create 360-degree virtual camera environments and handle resource-intensive tasks like green screen video capture directly on location, completely transforming the economics of remote production.
Energy operations demand speed, precision, and resilience in remote and rugged locations such as offshore drilling rigs and overland exploration sites. Offshore rigs lack traditional IT infrastructure, relying on high-latency satellite communications (SATCOM) for data transmission, and exploratory teams often work in remote, power-limited areas for short durations, with limited visibility into whether data collection was successful until they return.
Gryf enables teams to capture, process, and act on critical data right at the edge, helping to prevent dangerous events offshore or validate drilling targets in real time during land-based surveys, processing data locally so that teams can act faster, improve safety, and maintain control over sensitive information.
Other applications for Gryf include:
• Healthcare/Medical Research, enabling diagnostic analysis and patient-critical decisions in clinical environments through its configurable, facility-ready design that processes data securely on-site.
• Scientific Research/Field Studies, empowering scientific breakthroughs directly at research sites through its configurable, field-ready design that processes complex data at the source.
• Industrial/Manufacturing, providing production analysis and process optimization directly at manufacturing operations through its configurable, factory-ready design that eliminates remote processing delays.
Gryf is now generally available worldwide and shipping through GigaIO’s global partner network.
