About ClydAI (pronounced Cloud AI)

Artificial intelligence has enormous potential, but adopting AI successfully is about much more than choosing the latest model. The interesting questions are usually harder: Where can AI actually make a difference? What should we build? How should it fit into the organization? And how do we do it responsibly? That's where ClydAI comes in.

We help organizations turn AI opportunities into real solutions. That can mean developing an AI strategy, evaluating emerging technologies, designing an enterprise architecture, building an AI platform, or helping an organization figure out how AI fits into the way it already works. Our work spans AI strategy, solution architecture, governance, evaluation, and AI transformation, across cloud, on-premises, and air-gapped environments.

The technology landscape is constantly changing. Organizations don't need to chase every change. They need to understand what matters for their business, where AI can create real value, and how to get that value without unnecessary complexity or spend.

ClydAI's work spans very different environments. That's intentional.

At a large federal civilian agency, ClydAI supported AI strategy and innovation across the organization. The work went well beyond policy. It included building the processes and infrastructure needed to move AI from ideas into an operating capability, including use case intake and evaluation, governance, AI adoption, reporting and performance frameworks, and the evaluation of emerging AI technologies. It also meant thinking about what was coming next and how an organization should prepare for rapidly changing AI capabilities.

AI looks very different when your environment is highly constrained. ClydAI is working with an aerospace engineering organization that operates in secure, predominantly on-premises and air-gapped environments to develop a practical path to AI adoption.

That means figuring out what belongs inside the organization's environment, how models and AI infrastructure should work together, where AI can immediately help the engineering team, and how to create an architecture that can eventually support customer-facing AI solutions. This isn't simply about deploying a model. It's about designing an AI strategy around the environment the organization actually has.

ClydAI is also building an AI platform for specialty medical practices. The idea came from a simple observation: practices already have enormous amounts of operational data, but much of the work that happens around it is still manual.

The platform is designed to help practices identify and act on opportunities across administrative workflows, follow-up, billing, and revenue operations. The goal is not to add another dashboard. It is to put AI to work on the work that people don't have time to do.

Hi, I'm Khyati Nayak.

I've spent more than two decades working across software engineering, management consulting, and enterprise technology.

I've always been drawn to the space between what a business needs and what technology can actually do. AI makes that space particularly interesting because the technology is changing so quickly. The challenge is separating what is genuinely useful from what is simply new. My work in AI has taken me from federal AI strategy and governance to enterprise architecture in highly constrained environments and the development of AI products for healthcare.

I founded ClydAI because I wanted to work on those problems directly: finding the opportunity, figuring out what should be built, and helping make it real.