A maritime IT veteran is applying two decades of shipboard infrastructure experience to a very different problem: keeping enterprise AI on an organization’s own turf.
Ships used to be isolated. You’d hand over a vessel to its crew and it would more or less disappear until it showed up at the next port. That’s not really true anymore. A modern vessel throws off constant streams of operational, maintenance, safety, and performance data, and shipping companies are still figuring out what to do with all of it. Mohanraju Muppala has spent the better part of the last decade in the middle of that problem, first as an IT manager working directly with fleets, and more recently as someone trying to solve a related question in a completely different setting: enterprise AI.
Muppala has over 12+ years in vessel IT infrastructure, enterprise applications, and maritime cybersecurity, with stints at Clipper Fleet Management, Ultraship ApS in Denmark, and Maersk Tankers under the Synergy Group umbrella. At synergy Fleet he managed IT and application delivery across a fleet of more than 600 vessels, which is the kind of scale that forces you to think in systems rather than one-off fixes.
That’s more or less what he did with GreenCore, a vessel IT infrastructure initiative he led the design and rollout of at Clipper Fleet Management, Ultraship ApS Synergy Fleet vessels. The project combined sustainability goals with cybersecurity and standardization work, and according to its own documentation it was built to cut energy use by around 18% and uptime 98% compared to older shipboard IT setups. It also gave shore-based teams visibility into what was happening on individual vessels, something that sounds obvious until you consider how disconnected fleet IT often is in practice.
Connectivity was the harder problem, honestly. Vessels don’t have the luxury of a fast, cheap internet connection the way an office does. Satellite bandwidth is limited and expensive, so any digitalization effort at sea has to be built around that constraint rather than pretending it doesn’t exist. Muppala’s work on VSAT and satellite communications, spanning Inmarsat, Marlink, Starlink, FBB, and the various L, Ku, and Ka-band systems, comes out of exactly that reality. He’s also led full infrastructure buildouts across fleets of 25 or more vessels, handled ERP rollouts, built out Planned Maintenance System databases from scratch, and implemented ISO 27001-aligned security frameworks that had to work both onboard and onshore.
A different kind of infrastructure problem
Lately Muppala’s attention has shifted toward enterprise AI, and the connection to his maritime background isn’t as much of a stretch as it might first appear. The question he’s working on now is basically the same one: how do you give an organization real technological capability without forcing it to hand its data over to someone else?
That’s the idea behind Shreembo, an AI platform he founded that’s built to run on an organization’s own infrastructure, whether that’s on-premise or a private cloud, instead of routing sensitive information through a third-party service. The platform includes secure retrieval-augmented generation, AI-assisted project management, audit and administration tooling, document processing across multiple formats, and integrations with existing ERP systems and APIs.
It’s aimed at the kind of organizations that can’t afford to be casual about where their data ends up: shipping and logistics companies dealing with cargo and routing information, healthcare providers, government agencies, anyone in a regulated industry handling proprietary or compliance-sensitive records. For maritime operators specifically, that means things like technical manuals and vessel documentation staying inside the company rather than sitting on someone else’s servers.
Alongside Shreembo, Muppala has also built out Bounce Board, an AI tool meant to look at an organization’s operations, flag where the gaps are, and suggest ways to improve efficiency or cut costs. It’s less about replacing human judgment and more about giving decision-makers something concrete to work from.
Research on the side
Muppala also publishes. His Google Scholar profile shows more than 70 citations, with research touching on AI’s role in climate modeling, machine learning applications in maritime shipping, and cybersecurity in logistics. He’s listed as an author on IEEE, and in 2025 he put out two books through Deep Science Publishing: *Digital Oceans: Artificial Intelligence, IoT, and Sensor Technologies for Marine Monitoring and Climate Resilience*, and *SQL Database Mastery: Relational Architectures, Optimization Techniques, and Cloud-Based Applications*. Not exactly light reading, but it fits the pattern of someone who likes to write down what he’s learned rather than just move on to the next project.
There’s a thread running through all of this that has less to do with maritime technology or AI specifically and more to do with how Muppala approaches problems generally. Limited bandwidth, tight budgets, strict compliance rules, crews spread across the globe: none of that goes away just because the technology gets more advanced, so the infrastructure has to be built around those constraints rather than in spite of them. As shipping companies keep moving away from fragmented, manually run systems toward something more connected, people who understand both the maritime side and the technical side of that shift are going to matter more, not less.
More on Muppala’s research is available through his Google Scholar profile. Shreembo can be found at shreembo.com.
