Our Mission

The Promise of AI

It feels like Large Language Models (LLMs) are taking over the world. LLM providers make AI sound like a panacea that will solve all your problems. The reality is that building AI applications is hard.

Indeed, if an AI can easily solve your business problems, then you very shortly won't have a business. While AI holds great promise, we're confident that it won't replace you—if you can harness it.

Our mission is to help you achieve your AI requirements.

What do you care about?

When we talk with AI application builders, we always start with same question:

What do you care about?

Answers vary depending on how far along builders are into their AI development journey. But there are common themes, usually along the lines of:

I want it to be fast.
I want it to be accurate.
I want it to be affordable.
I want it to be reliable.

Even before we consider these requirements further, it may already be obvious to you they are in tension with each other. English speakers are familiar with the phrase, "You don't get something for nothing." The same is true with AI—and computing more generally—there are tradeoffs to be made. This leads to our follow-up question:

What do you really care about?

In other words, start prioritizing.

Speed can means different things. Latency, or wall-clock time matters, like the time-to-first-token or the complete response time. Throughput, or data rate, also matters, like tokens per second or requests per minute.

Accuracy—sometimes called performance—is critical, but often poorly defined. An entire ecosystem of LLM Evals exists to help measure AI model responses. Common topics include answer relevancy, correctness, tone, bias, and toxicity, but this list is far from complete.

Affordability is better-understood, but difficult to control in practice. We constantly hear from product managers how difficult it is to project their AI costs. Even for well-defined applications, variability in LLM request and response sizes, counts, and modalities exacerbates the problem.

Reliability is a standard feature in most services, but sorely lacking in the AI space. Real-world applications have strict availability requirements, often with service-level agreements—business depends on it. AI services similarly need to be consistent, not just for availability, but also for the dimensions just discussed.

The Adaptive AI Orchestration Platform

If you're building applications with AI, you almost certainly have requirements like those described above, even if you've had difficulty defining or expressing them. Now you've come to the right place and are talking to the right people.

Addressing the above requirements is already difficult in relatively static environments. But, the AI landscape is evolving at a remarkable pace. New models—and even new providers—are constantly arriving and disappearing. Model deployment runtime behaviors are highly variable. User workloads change suddenly. Applications have to regularly re-evaluate their priorities to keep up.

At Influxion, we're experts in adaptive systems. Unlike traditional software that is highly tuned during development phases (at great engineering effort at cost), adaptive systems respond in real-time to evolving conditions without the need to redesign or rewrite applications. They self-correct to satisfy high-level requirements without developer intervention. We believe that adaptive systems are the ideal solution for deploying AI applications today and are the future for AI-enabled services.

Welcome to Influxion! Get started today.