Unified SASE as a Service – Safely Delivering GenAI Applications at Scale

It’s a few weeks after the RSA Conference in San Francisco, which is always a great opportunity to reconnect with peers and learn about the latest developments in the security space. Often, there is a theme or topic that dominates the event, and 2024 was no different. Across all my conversations, the most common buzzwords were AI, AI, and AI. And the question I got the most? ‘What is Aryaka’s AI strategy?”  My answer came in three parts: the 3 pillars of the Aryaka Unified SASE as a service solution: networking, security, and observability.  In other words, our strategy is fundamentally to enable and accelerate the performant and secure use of AI applications across our customers’ global networks.

Pillar 1: Networking

AI opens massive possibilities for companies, provided they have the network bandwidth to activate the benefits. Large language models (LLMs) require massive amounts of data transfer and thus, massive amounts of bandwidth. The burden falls on the network to transfer this data and when the network capacity falls short, it can harm the core functions of the business. I’ve even heard of companies flying hard disc data storage on a plane across continents because their WAN connection and bandwidth are too slow and unreliable to confidently transfer LLM data. At Aryaka we offer WAN optimization, de-duplication, and queuing where we can help customers devote a fixed portion of their bandwidth for secure AI data transfer, protecting their daily business operations from network overload. Flying hard discs around the world is not a sustainable business practice – and having a network you can trust to process all of your data is the first step to unlocking the vast benefits of AI.

Pillar 2: Security

Another challenge of AI, as with any new and seemingly beneficial development, is the opportunity for bad actors to exploit it. For our customers, we must secure the new attack surface that AI opens up to make the benefits worth pursuing. Three initial steps include:

• Access control: How do we ensure that people accessing GenAI Apps are the right people?
• Threat protection: How do we secure AI infrastructure and GenAI applications from external attacks such as data poisoning, supply chain vulnerabilities, and prompt injection, respectively, including other variants?
• Protecting intellectual property: Much like DLP (data leakage prevention), I heard the term KLP (knowledge leakage prevention) for the first time at RSA this year.

Each of these factors are focal points for Aryaka’s Unified SASE as a Service in securing AI infrastructure and operations against exploitation.

Pillar 3: Observability:

Having safe and performant AI applications is no doubt highly valuable, but to improve those apps over time you must have insight into what is being used and by whom. Whether it’s development tools or marketing tools, companies need to understand which AI resources are most popular with their users in order to optimize their future efforts. Working with a Unified SASE provider like Aryaka, companies can access and observe all their traffic to better understand which users are using which tools and why.

In conclusion, at Aryaka, we see our role in the AI landscape as enabling companies to unlock, secure, and understand the usage and benefits of AI. That’s exactly what our Unified SASE as a Service offering is designed to do.  In fact, we believe the future and success of AI across enterprise networks demands the implementation of a Unified SASE as a service solution.

Over the next months and quarters, we will share more specific product news and even more importantly, insight into our customers’ needs and how they are better enabling, securing and understanding the use of AI across their networks and businesses.