Praruh Technologies Ltd., a BSE-listed ICT and system-integration powerhouse that has rapidly emerged as the trusted digital-transformation partner for the nation’s most critical sectors. Founded in 2019, Praruh is actively modernizing legacy IT environments across high-impact domains—from aviation and railways to defense. With a sprawling operational footprint supporting infrastructure giants like DMRC, RailTel, ONGC, and the Airports Authority of India, the company delivers end-to-end solutions spanning data-center deployments, enterprise networking, and advanced cybersecurity.
Steering the technological vision behind these massive public and enterprise deployments is Amardeep Sharma, Chief Technology Officer and Director at Praruh. With nearly two decades of deep-rooted expertise in unified communications, network architecture, and complex system integration, Amardeep is the architect bridging the gap between ambitious government tenders and seamless, future-ready execution. Having driven enterprise network transformations at industry stalwarts like HCL Infosystems and Polycom, he brings a unique blend of strategic solution design and hands-on operational leadership.
In this edition of TechStoriess, we sit down with Amardeep to unpack the immense complexities of upgrading India’s mission-critical infrastructure, the evolving landscape of enterprise security, and the strategic roadmap for building resilient digital ecosystems from the ground up.
What motivated you to start Praruh back in 2019?
When we started Praruh in 2019, we wanted to build a technology company that was actually solving customer problems rather than simply selling products. At the time, we saw many organisations working with multiple vendors for different parts of their IT infrastructure, and that often created more complexity.
We started with IT and infrastructure solutions and, over time, expanded into areas such as networking, data centres, storage, security and digital transformation. The business has grown since then, but our approach hasn’t really changed. We still start with the customer’s requirement and then look at the technology that makes the most sense for them.
How did your communications background shape Praruh’s startup journey?
My background in communications gave me a strong understanding of how important connectivity and reliability are to an organisation. Technology keeps changing, but the basic requirement is still the same — people, applications and data have to communicate reliably and securely.
That experience helped us when we began taking on larger infrastructure and system integration projects. As customer requirements evolved, we moved beyond traditional networking into data centres, storage, security and digital transformation. Today, with AI becoming a bigger part of enterprise IT, that understanding of connectivity and integration has become even more relevant.
How does your platform unify workforce intelligence and hybrid work?
We don’t really look at it as a standalone platform. For us, it is about bringing different parts of the technology environment together.
With hybrid work, employees are accessing applications and data from different locations, devices and networks. That makes connectivity, security and visibility increasingly important. Our role is to help bring these layers together so they function as one environment.
We are also seeing more organisations use analytics and AI to understand infrastructure usage and employee experience. Ultimately, the objective is quite straightforward: give IT teams better visibility while making the working environment more reliable, secure and seamless for employees.
How do you ensure privacy compliance for global SaaS platforms?
Privacy has to be considered right at the beginning of any technology implementation. We first look at what kind of data is being handled, who needs access to it and where that data is stored or transferred.
Based on that, organisations need to put the right access controls, security measures, monitoring and governance in place. With SaaS and cloud platforms, it is also important to clearly understand what the customer is responsible for and what sits with the service provider.
There isn’t a single approach that works for every organisation. We work around the customer’s security framework and the regulatory requirements that apply to their business.
How is AI changing enterprise IT infrastructure design and management?
AI is changing the way infrastructure needs to be planned. Traditional enterprise workloads were relatively predictable, whereas AI workloads can demand significantly more compute, storage, data movement and network capacity.
But the change isn’t only about adding more hardware. AI is also changing how infrastructure is managed. We can use AI to analyse utilisation patterns, identify unusual behaviour and potentially flag issues before they become major problems.
So infrastructure is gradually moving from being something that simply supports applications to becoming a more intelligent and actively managed part of the IT environment. I think that will be a major shift for enterprises over the next few years.
How do we prepare legacy infrastructure for AI without disruption?
I don’t think the answer is to replace everything. For most enterprises, that would neither be practical nor financially sensible.
The starting point should be an assessment of the existing infrastructure. You need to identify where the actual bottleneck is. It could be the network, storage, compute, data architecture or security layer.
Once those gaps are understood, organisations can modernise in phases. In many cases, existing investments can continue to be used while new capabilities are introduced alongside them. That gives enterprises a way to prepare for AI without putting ongoing business operations at risk.
How can AI observability improve infrastructure performance and predict failures?
Traditional monitoring generally tells you when something has gone wrong or when a particular metric has crossed a threshold. AI can take this a step further by looking at patterns across large volumes of infrastructure data.
For example, it can identify behaviour that may suggest an issue is developing before it results in an outage. It can also correlate information across networks, servers, storage and applications, which is difficult for teams to do manually.
That can help reduce troubleshooting time and, more importantly, move IT teams from a largely reactive approach towards predictive maintenance.
What infrastructure and governance support agentic AI workflows at scale?
Agentic AI is going to require a strong infrastructure foundation because these systems can do more than just generate information. They may be able to take actions within enterprise systems, which makes governance and security particularly important.
Enterprises will need scalable compute, reliable data platforms, high-performance connectivity and strong observability. At the same time, they will need clear controls around identity, access and the actions an AI agent is permitted to take.
There also needs to be accountability. Our view is that enterprises should put these guardrails in place early and then scale their agentic AI initiatives. Moving quickly is important, but doing so without adequate controls can create larger problems down the line.
How does Praruh bridge legacy environments with AI and automation?
Most enterprises today are working with a mix of legacy systems, newer infrastructure, cloud platforms and technologies from different vendors. So, the reality is that very few organisations can simply start from scratch.
We begin by understanding how the existing environment works and where integration or automation can make a meaningful difference. Depending on the requirement, that could involve an API or integration layer, or it could mean upgrading parts of the network, storage or compute environment.
The objective isn’t to replace technology simply for the sake of modernisation. If something is working well, we look at how it can continue to be used while connecting it with newer technologies.
What differentiates Praruh’s AI infrastructure approach for Indian enterprises today?
One thing that stands out in India is the wide variation in technology maturity. Some enterprises are already making significant investments in AI, while others are still working on modernising their data centres or upgrading legacy infrastructure.
So, we don’t believe there is a standard AI infrastructure blueprint that can be applied to every organisation. We first look at the customer’s existing environment, business requirements and investment priorities, and then build a roadmap accordingly.
Our experience in system integration across networking, storage, security, data centres and other infrastructure areas gives us a strong base. We see AI as the next stage of that infrastructure journey rather than something completely separate from it.
Can you share details on Praruh’s current revenue and funding?
Praruh has grown largely through customer relationships, enterprise engagements and government technology projects. We have focused on building the business organically, while steadily expanding our capabilities and strengthening our relationships with technology partners.
For FY 2025–26, Praruh recorded a revenue of ₹101.61 crore. Over the years, we have expanded our portfolio across infrastructure, networking, data centres, storage, security and digital transformation.
As the demand for AI infrastructure continues to grow, we are evaluating opportunities to further expand our capabilities, partnerships and presence in the market. Our focus remains on sustainable growth and building a strong technology business for the long term, rather than pursuing growth purely for the sake of scale.
What is Praruh’s vision for next-generation intelligent enterprise IT infrastructure?
Enterprise infrastructure is becoming much more integrated. Traditionally, compute, networking, storage, security and applications were managed as separate layers. That model is gradually changing.
Going forward, these systems will need to work together much more closely, with AI helping enterprises automate processes, optimise resources and identify issues before they affect operations.
Our vision at Praruh is to help enterprises make that transition without having to discard everything they already have. We want to help customers modernise their existing environments, build the right foundation for AI and gradually move towards infrastructure that is more automated, resilient and responsive to business requirements.
