Artificial Intelligence (AI) is everywhere. From headlines to boardrooms, it’s the topic on everyone’s mind and every company’s roadmap. The promise of AI capabilities is clear: power real-time decision making, drive smarter decisions, innovate faster, and create better customer experiences. But realizing that promise, especially at the edge, is a different story.
Some teams are busy debating AI ethics and risks. Others are rolling up their sleeves, racing to build AI-driven systems that deliver a competitive edge. For those in the latter camp, one challenge looms especially large: how do you make AI work in the unpredictable, high-friction environments where edge computing, Internet of Things (IoT) devices, and real-time data processing are critical?
The Challenge: Making AI Work at the Edge
Edge environments, like retail stores, remote offices, factories, or vehicles, are notoriously tough. Unreliable connectivity. Limited compute and storage. Constant integrations. Inconsistent infrastructure. These are not the ideal conditions for deploying high-performance AI.
Yet, this is exactly where real-time AI can deliver the most value: smarter operations, faster decisions, lower costs, and improved compliance. The problem? Most data movement and synchronization tools simply weren’t built for these conditions.
Deploying AI algorithms and machine learning at the edge introduces a unique set of challenges—from large model sizes to unpredictable networks. To succeed, teams must ensure fast, reliable, and secure model and data distribution, with automation to streamline updates and management, across globally distributed edge locations.
Key Challenges:
- Distributing large AI models (MBs to GBs) over limited, intermittent edge networks
- Ensuring consistent model versions and atomic updates to avoid corrupted inference
- Managing and syncing large volumes of training data (video, logs, sensors) while meeting privacy and compliance standards
- Maintaining and optimizing inference reliability during outages—with rollback and recovery built in
The Resilio Advantage: Built for Edge Computing Use Cases
Peer-to-peer (P2P) architecture is purpose-built to meet the unique demands of edge AI. Whether distributing large AI models or collecting continuous training data, Resilio ensures fast, reliable, and bandwidth-efficient synchronization across edge devices—no matter how constrained or disconnected they are. From delta-based sync to offline resilience, Resilio keeps AI pipelines running smoothly, even at scale.
Key Benefits:
- Fast, Efficient Model Distribution: Delta sync and P2P architecture speed up large model deployment while minimizing bandwidth usage for AI workloads
- Reliable Data Ingest: Bidirectional, real-time sync supports continuous learning and data collection—even during outages
- Staged Deployment with Rollback: Health-checked updates prevent failed rollouts and maintain version consistency
- Always-On Operation: Offline and low power support and automatic retries ensure uninterrupted deep learning inference and training
- Enable Predictive Maintenance: Leverage real-time ingestion of IoT devices sensor data to detect anomalies, forecast equipment failures, and optimize maintenance schedules—reducing downtime and costs across all edge locations.
Resilio at the Edge: Scaling Ship-to-Shore IT with Resilio Active Everywhere
As one of the world’s largest and most trusted ship management companies, Synergy Marine Group needed a better way to deploy software, updates, and business-critical files across a global fleet of 700 vessels—without relying on unreliable satellite connections, USB drives, or manual processes. With Resilio Active Everywhere, Synergy transformed its ship-to-shore IT operations, achieving massive improvements in speed, scalability, and operational resilience.
Key Results & Benefits:
- Cut deployment time from one vessel per day to over 600 vessels in just 2–3 days
- Automated over 2,000 deployments and synced 32TB+ of data without manual effort
- Replaced USB-based updates with real-time ship-to-shore sync over satellite links
- Reliable transfers that resume automatically—no babysitting or failed syncs
- Boosted stakeholder confidence with faster, more secure IT delivery
- Lowered costs by reducing manual work and using existing infrastructure
Powering the Future of Edge AI
Resilio Active Everywhere is the only platform that delivers real-time, secure, and resilient data movement at a global scale, without relying on fragile network dependencies or central bottlenecks.
With Resilio, you can:
- Seamlessly ingest, deliver, and synchronize data across data centers, cloud, and edge environments
- Eliminate single points of failure
- Operate reliably in low-bandwidth and high-latency conditions
- Support thousands of edge endpoints with complete visibility and control
- Optimize AI capacities and CPU, GPU, and specialized processor utilization for complex edge AI workloads
If your organization wants to unlock the power of AI applications at the edge, Resilio delivers the foundation you need, fast, flexible, and built for scale.
Ready to see how Resilio empowers AI at the edge? Schedule a demo today.
