Q: What shaped Elitery’s evolution from data centers to AI? 

Kresna Adiprawira, founder and president director of Elitery: My time working in the U.S. was formative. I spent eight years there after graduating in 1999, working at a startup, and what struck me was how Indian entrepreneurs had built globally competitive technology companies. That became a personal motivation—why couldn't Indonesians do the same? 

I returned to Indonesia in 2007 and immediately began doing remote work for my former U.S. employer. That model—delivering services from Indonesia for international clients—became the blueprint. By 2011, I saw a clear need for a certified, independent data center in Indonesia, and we launched Elitery. Within our first year, we became the first data center in Southeast Asia to receive Tier III certification from Uptime Institute. 

The next pivotal moment came in 2017. The market had been flooded with new data center capacity—much of it backed by telcos and large conglomerates—and pricing had compressed to the point where an independent operator couldn't compete on infrastructure alone. I had been watching cloud adoption closely through my continued ties to the U.S. market, and it was clear that was where the industry was heading. So we pivoted away from physical data center operations and toward cloud managed services, partnering with AWS and later Google Cloud, and beginning to educate the Indonesian market about what cloud could do.

COVID-19 accelerated everything. Overnight in 2020, every government ministry, every enterprise and every institution needed to move online. Supply chains for hardware were disrupted, and cloud was the only viable path. Because we had been advocating for cloud adoption for three years, we were already top of mind. We grew almost exponentially from 2020 through 2024, nearly doubling revenue each year. 

Now the next crossroads is AI. We went from data center to cloud in 2017, and we're now making the transition from cloud managed services to managed AI services—specifically agentic AI. We're building tools to help enterprises deploy, govern and manage AI agents running autonomously across their operations. The managed service DNA stays the same; what we're delivering on top of it is evolving. 

Q: How does Google MSP status sharpen Elitery’s advantage? 

KA: The Google MSP designation is meaningful precisely because of how difficult it is to obtain and maintain. It's invite-only, requires Premier Partner status as a baseline and then involves a rigorous two-day audit across people, processes and technology—roughly 500 assessment points—to confirm you can deliver services to Google's own global standard. We renew it annually. That puts us in the same tier as the major global consulting firms that hold this designation, and there are fewer than 70 of them worldwide.

What it gives us is confidence to compete globally, not just in Indonesia. Cloud services are inherently borderless—we can manage a client's infrastructure from Jakarta as effectively as from London or Singapore. Having built a strong foundation in Indonesia, with the certifications, the processes and the experienced team to back it up, it would be a missed opportunity not to expand. We're now operating in Malaysia through a local subsidiary, and we're actively evaluating entry into the European market as well. 

Q: How are you positioning Elitery among global stakeholders? 

KA: I want Elitery to be understood as a company with institutional-grade service delivery, deeply embedded client relationships and a proven model that can be replicated across markets. We're not a local player that got lucky—we built something durable, and we're taking it global. 

Q: What is driving Elitery’s recurring revenue growth? 

KA: The recurring revenue model reflects the nature of managed services done well. Our average client has been with us for at least three years, and we have roughly 40 to 50 clients who have been with us since the early days—in some cases close to 15 years. That kind of retention only happens if you're consistently delivering.

The sales cycle for a new client typically runs six months or more. That's a significant investment, but it's justified when the relationship generates recurring revenue year after year. Once a client trusts you with their infrastructure, they don't leave lightly. 

The growth strategy going forward is essentially replication. We have a strong, certified, audited service delivery team in Indonesia. The model works. We apply it in Malaysia; we'll apply it in new markets. We're not reinventing anything—we're taking what we've built and expanding its footprint. 

Q: How is Elitery working with the public sector?  

KA: Indonesia has an experimental culture that is genuinely well suited to this moment in AI development. Enterprises, government agencies and even provincial governors are willing to try new technology, see what works and build from there. That's a significant advantage. There's a go-getter mentality in Indonesia that mirrors how Silicon Valley operated in its early years: deploy, learn, iterate.

The West Java student counseling project is a good illustration. The governor recognized that students were often reluctant to open up to human counselors about their academic performance and future options, but they would engage candidly with an AI. Our PandAI platform—integrated with student academic data from the government—was able to provide personalized, contextually aware guidance at scale. Students can consult the AI counselor for college major consultation, scholarship recommendation and university recommendation. It reached 50,000 students last year, and the response was strong enough that implementation is being extended.

What that tells us is that AI in Indonesia isn't just a corporate buzzword. It's being applied to real social challenges, at scale, with government backing. That creates enormous opportunities for companies that can help organizations deploy AI responsibly, securely and cost-effectively.

Q: How is Elitery preparing for agentic AI? 

KA: Agentic AI is going to create a new category of operational risk that most organizations aren't prepared for. We're already seeing the early stages of what I'd call "shadow agentic AI"—business units deploying autonomous agents outside of IT governance, automating workflows without anyone having full visibility into what those agents are doing or what they're costing. 

That's exactly the problem managed services were built to solve. In the same way that we help clients manage their cloud infrastructure—ensuring it's running efficiently, securely and within budget—we're building tools to manage fleets of AI agents. Who authorized them, what are they accessing, how much are they costing, are they operating within policy? Those are the questions that will keep CIOs up at night as agentic AI proliferates, and we intend to be the answer. 

We're not building AI models, and we're not competing with foundation model providers. We stay in our lane—managed services—but we're expanding what "managed" means to include the AI layer that is increasingly running on top of the cloud infrastructure we already manage. 

Q: Why is talent development central to Elitery’s strategy?  

KA: Talent was a problem we ran into internally before it became a strategy. During our rapid growth phase around COVID, we were hiring and training fresh engineering graduates, only to have them recruited away by well-funded unicorns after six months. We'd made the investment; someone else was capturing the return.

That led us to think about building a training infrastructure we could control and eventually monetize. When AWS approached us about delivering a government-backed digital skills program in Indonesia, funded by USAID, it aligned directly with what we were already working toward. We built Elite Mentor, our AI-powered training delivery platform, specifically to handle the scale required. 

The program we are working on with AWS is the CendekiAwan program in Malaysia, which is running on the same model. Batch one covered 20,000 students; batches two and three will bring the total to around 130,000. Beyond the social impact, this builds a pipeline of AI-certified talent that benefits the broader ecosystem—including Elitery's own hiring. 

Q: What differentiates Elitery from its competitors? 

KA: From a competitive standpoint, the Google MSP designation is the most objective differentiator we have. We believe we're currently the only company in Indonesia holding that designation, which means our service delivery capability is, by definition, at a global standard. But beyond the certification, what sustains clients over 10 or 15 years is consistency—the sense that you understand their environment, anticipate their needs and aren't going to disappear when something goes wrong. 

The model we're taking into Malaysia and other markets is the same one we built in Indonesia: start as a trusted partner, deliver consistently and grow with the client. It's not complicated, but it requires patience and a genuine long-term orientation.

Q: Why should investors consider Indonesia’s cloud and AI sector? 

KA: Indonesia's fundamentals are compelling. You have a population of over 270 million people, a growing middle class, a government that is actively investing in digital infrastructure and a private sector that is willing to experiment. The demand curve for cloud and AI services has not yet reached its inflection point—we're still in the early stages of enterprise adoption. 

What makes the timing particularly interesting is the convergence of several trends: government digitalization mandates, a maturing startup ecosystem that is generating enterprise-grade technology demand and the arrival of hyperscalers—Google, AWS, Oracle and IBM—who are committing serious infrastructure capital to Indonesia. That creates a rising tide for companies that can help enterprises implement and extract value from these platforms.

The opportunity we see is specific: most organizations in Indonesia and across Southeast Asia need a trusted, locally embedded partner to help them navigate cloud and AI adoption. They don't just need a license—they need governance, security, ongoing optimization, and, increasingly, management of the AI layer on top. That's the gap we fill, and the market for it is growing faster than the supply of companies equipped to serve it well.