The next critical component is multi-agent orchestration with an event-driven architecture, together with a Pub/Sub mechanism that is 10 times faster than other similar solutions. In addition, Adya built a framework that eliminates the need for a central orchestrator, where each agent is fully autonomous and can decide whether to perform the task, propagate it to another agent, or create a new agent.

As for application creation, Mazumder points to what the team calls App Studio. "What we've done is we have created a sequence of AI agents. One handles UI/UX, another handles business requirement documentation and so on for system architecture document generation, backend and frontend coding, QA testing, and deployment. That means you can now actually go and have a chat with the AI, it will understand what you're trying to do, and create the entire application for you," said the founder.

"Something that used to take us months to do – three, four, sometimes 10 developer months – today, can be done in one hour or even 15 minutes. The App Studio difference is that other platforms are not able to build agents. More importantly, our platform enables you to create the entire application and integrate it with your existing one."

For developers seeking an open-sourced approach, Model Studio is where they can choose any of the models and build a fine-tuned LLM. One such setup saw LLMs outperforming competitors by 21% at 85% lower cost.

Greater control can also be exerted through Adya's Cloud Studio, where users can deploy solutions on Google Cloud with granular control. Kubernetes clusters can be customized, virtual machines can be deployed, and security and tenant options can be adjusted. This provides complete visibility and observability over the cloud.

The final component for Adya’s system is the Adya’s Marketplace, where developers can launch and monetize their solutions built on the platform.

LLMs are harder to handle on the security front, and Adya utilizes Adaptive Learning Protocols (ALPs) for every user query to determine whether it has system or data-level implications. The protocols determine whether access rights are being violated before any information is shared. 

All data is handled responsibly in terms of storage and use, a point that Mazumder is keen to emphasize. "The ALPs ensure that there is no wrong interpretation of laws, processes, or SOPs. Beyond that, we use guardrails to ensure that AI is not doing something unethical. Everything goes through the battery tests. Responsible AI use comes into play on multiple levels, so you have to look at ethical considerations, and you have to look at observability. So we have set up an entire observability suite, we've set up the ALPs, and all of this together combined to create responsible AI use at Adya," Mazumder explains.

With Adya's position and potential to help, the team understands the value of extending a helping hand with AI to those who can benefit greatly. Mazumder shares that the company is "mindful that AI has to reach every last corner" and, to that end, is providing complete and free access to the entire platform for organizations such as Headstart, which supports startups, universities, developers, and female entrepreneurs, to reach the next level of their growth.

"AI allows you to create systems that natively behave like humans. So if you're able to talk to it, then you don't need to learn how to use it. So that entire layer goes up, and that is where AI is bringing in a sea change in adoption," concluded Mazumder.

Adya is well-positioned to continue building on its successes. With even more products due to launch in the coming months, and with further collaboration with Google, organizations looking to improve their working processes will soon have more options to choose from.