According to a study by Insight Partners and the MIT Center for Information Systems Research (CISR), businesses in the top quartile of “real-time-ness” significantly outperform their peers:
- 62% higher revenue growth
- 97% higher profit margins
These organizations also demonstrate improvements in operations:
- Innovation: 20% better
- Operational efficiency: 22% better
- Risk management: 17% better
These findings emphasize the importance of becoming a real-time business. Operating in real time isn’t just about speed—it’s about aligning agility with scale, accuracy, and innovation. Notably, these profit margins weren’t achieved by being agile at any cost. Building a real-time business must also account for cost efficiency that is sustainable at scale, while supporting a “future-proof” tech stack capable of working seamlessly with any vendor.
Mission impossible? Not when the foundation of that tech stack—the network—is enabled with pure software and sub-microsecond accuracy. But before diving into how that works, let’s first define the “real-time business.”
Understanding the Real-Time Business Era
According to CISR and Insight Partners, a real-time business (RTB) is defined by its ability to execute and adapt to challenges and opportunities instantaneously. This means automated processes, trusted data, and empowered decision-making, all supported by strong governance. The goal isn’t just speed; it’s about making better, more efficient decisions.
For decades, terms like “digital transformation” aimed to achieve this holy grail, but the rapid adoption of AI has made real-time capabilities not just accessible but imperative for staying competitive.
Why the Network Matters
The network is the foundational layer of the “real-time operations techstack”. AI applications generate massive data traffic, demanding ever-increasing bandwidth and low latency for efficient data movement and processing. At the same time, workloads such as deep learning, generative AI, real-time data processing, and high-performance computing (HPC) applications—including simulations, pharmaceutical discovery, weather forecasting, and financial modeling—are becoming increasingly distributed and latency-sensitive.
Without the right infrastructure, even the most sophisticated systems risk falling short. Additionally, the costs of upgrading to an entirely new network infrastructure can be prohibitive.
Clockwork.io addresses these challenges with pure software that retrofits any existing networks, no matter how distributed —whether on-premises, in the cloud, or across hybrid and multi-cloud environments. By enabling high-precision clock synchronization, Clockwork.io dramatically reduces latency and the associated job completion times of GPU-accelerated applications, ensuring predictable and robust network performance capable of scaling to meet the demands of real-time distributed workloads.
How Clockwork.io Supports Real-Time Operations
Clockwork.io plays a critical role in optimizing real-time distributed workloads. Here are some examples:
- Precision Timing in Critical Environments
- Clockwork.io’s advanced synchronization technology is indispensable for latency-sensitive industries like high-frequency trading (HFT) and crypto arbitrage, where even microsecond delays can have significant consequences.
- Resolving Network Congestion in Kubernetes
- Kubernetes enhances scalability but can obscure underlying network congestion. Clockwork.io identifies and mitigates these bottlenecks, ensuring consistent performance.
- Efficient Timestamping Across Networks
- High-accuracy timestamping is typically costly and hardware-intensive. Clockwork.io offers a cost-effective, software-based alternative that delivers accuracy without requiring extensive infrastructure upgrades.
- Monitoring and Addressing Cloud Provider Throttling
- Cloud provider throttling often undermines application performance without clear visibility. Clockwork.io detects and addresses these inefficiencies, ensuring uninterrupted data flow.
- Scaling AI and Distributed Workloads
- Distributed workloads, including AI models and databases, rely on managing one-way latency for real-time performance. Clockwork.io provides tools to measure and optimize latency, enabling systems to scale efficiently, reliably and predictably.
Moving Toward Real-Time Business Efficiency
Transitioning to a real-time business no longer requires complex overhauls or uncertain investments. By understanding the measurable value of real-time capabilities today and leveraging cost-effective solutions like Clockwork.io, organizations can confidently achieve real-time performance using their existing infrastructure.
The real-time business era is here, and with the right tools and strategies, it’s more attainable than ever.