How Advaiya’s Peripheral Automation Redefines Enterprise Efficiency

Traditional automation has for many enterprises been a painful experience due to high costs and disruptions created by conducing a rip-and-replace of their legacy ecosystems. Advaiya's approach of Peripheral Automation presents a better, lower risk alternative to these headaches by improving parts or adding to the current architecture.

This approach decomposes enterprise architecture into three primary distinctions: experience, the business process and the core data integrity that will always have the least change and risk to manage. 

Advaiya's approach enables enterprises to innovate and modernize the experience and business processes of the architecture while enabling the enterprise core to remain stable and the company ships business as usual.

According to Manish Godha, Founder & CEO of Advaiya, AI benefits Peripheral Automation because it improves the efficiency, increases the speed of automation, and improves decision-making outcomes. From site surveys performed by AI, to automatic invoice processing the applications in real life demonstrate how businesses can achieve increased agility, scaling and success while avoiding ongoing disruption of critical operations.

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How does the Peripheral Automation Approach enhance traditional automation frameworks?

The Peripheral Automation approach changes the way that companies think about their enterprise architecture. Where previously 'rip and replace' strategies dominated—it often caused high costs, extended time frames, and operational “fears” or disruptions during implementation. The Peripheral Automation approach nudges toward an incremental, risk-sensitive value-adding strategy that relies more on enhancement over replacement.

The framework sees enterprise information systems as a three-layer enterprise architecture—experience and interaction, business process, and data integrity foundation. The experience layer focuses on customer, employee, and partner interactions, thus requiring agility.

The process layer supports internal workflows and business processes, emphasizing efficiency and integration. While the core entity layer houses foundational systems and application logics, prioritizing stability, compliance, and security.

This layered architecture allows businesses to innovate at the edges, thus avoiding destabilization of core systems and enabling efficiency of automation efforts with agility and effectiveness. With targeted enhancements rather than wholesale replacements, organizations can realize measurable efficiencies, with scalability and minimal disruptions.

What role does AI play in optimizing its efficiency?

AI does play a crucial role when it comes to using the Peripheral Automation approach to enterprise architecture. With the hype that AI and GenAI have seen over the past few months, the challenge that comes up is about investing smartly and wisely.  But with the Peripheral automation approach, businesses have the option to experiment through selective exposure within the organization.

AI is integral to optimizing the Peripheral Automation approach by enhancing flexibility, accelerating automation, fostering innovation, and improving customer experiences.

For instance, AI can enhance Peripheral Automation (PA) efficiency by enabling experimentation in the experience layer without disrupting core databases and application logic. By treating data flexibly, AI and PA can help seamless integration and real-time analysis, optimizing business and executive decision-making and business workflows.

Additionally, AI can accelerate the automation of tasks, foster continuous innovation through data insights, and personalize interactions, improving satisfaction and engagement.

Can you share an example of how AI-driven peripheral automation has improved operational workflows or decision-making in a real-world application?

For any enterprise there are a plenty of AI use cases, and the challenge is in selecting where the return is the highest and risk lowest. One example could be where we implemented Gen-AI based assistance to site survey and proposal creation for a large landscaping business. From an architecture perspective, it leveraged the customer and product database, as well as workflow processes already implemented.

This solution added a peripheral loop which gathered context from existing data, uses AI to augment the site survey report both in terms of language and precision. This AI driven interaction generated information which added to the existing workflow, at the same time bolstering quality and reducing effort immensely.

Another example is where Peripheral Automation has been used to automate the business process, where the accounts payable process is supported by AI based invoice processing—again built on existing accounting and SCM infrastructure.

How is your company helping customers deliver relevant business outcomes through the adoption of the company's technology innovations?

At Advaiya, we are committed to helping our customers realize measurable business results by aligning technology with strategic goals. Our methodology makes technology adoption not only about deployment but about creating measurable impact on efficiency, agility, and growth.

Our Peripheral Automation framework assists companies in mapping business models to technology layers so that the core applications are made strong while offering innovative process automation and dynamic user experiences. This systematic approach enables businesses to embrace digital initiatives in a manner that continuously provides value while improving overall technology maturity.

We've assisted businesses to streamline processes, enhance decision-making, and amplify customer experiences by implementing customized digital transformation programs. For example, in a recent engagement with a real estate business, we designed a centralized document management system incorporated into their CRM. This facilitated better accessibility, eliminated operational duplication, and facilitated compliance—bearing a direct effect on business efficiency and customer responsiveness.

Another example is where we have been implementing AI-powered analytics for manufacturing companies to manage production planning and job order monitoring. It anticipated delays and allowed making better-informed decisions, minimizing delays, and maximizing the utilization of resources.

Through ongoing innovation and improvement of our solutions, we make it possible for our customers to apply the latest technologies—including AI, automation, and data insights—to establish durable sources of competitive differentiation and generate valuable business results.

What is the future of peripheral automation beyond being a technical framework?

Peripheral Automation is transforming from a technical infrastructure to a strategic driver of agility, innovation, and long-term business value. It enables organizations to bring emerging technologies—AI, GenAI, ML, IoT, and automation—into their operations without upsetting core systems, so they can innovate fast while keeping stability intact.

Peripheral Automation is essentially a business alignment approach. It enables creation of technology roadmap which aligns with business priorities. The layered approach allows mapping business KPI’s with technology, and also identify where the return on technology innovation and investment is the highest.