Two focused, fixed-scope engagements designed to demonstrate tangible value quickly — without a long procurement cycle, without touching anything safety-critical, and without committing your fleet. Each is a starting point we shape around the questions you most need answered.
Your organization holds an enormous amount of knowledge locked inside documents — manuals, certificates, reports, correspondence and the institutional memory of your most experienced people. We take a defined body of that documentation and build an AI assistant that can read it, reason over it and put it to work: answering questions in plain language, drafting routine responses and surfacing what matters before it becomes a problem.
We begin by selecting one well-bounded workflow where the pain is sharpest and the documents are readily available. The pilot is built entirely around that selection — so the result speaks directly to a problem your team feels every week, rather than a generic demonstration.
Select the workflow, gather documents, define the success metric together.
Construct the knowledge pipeline and assistant over your document set.
Your team uses it on real work; we refine against their feedback.
Measured results, and a clear view of what fleet-wide rollout looks like.
Once trusted on one document type, the assistant extends naturally to others — and from retrieval toward action: routing, tracking and updating records automatically. A successful single-workflow pilot is the foundation for an organization-wide knowledge platform that learns across your entire operation.
We take one vessel and build the complete data foundation behind it — from the physical systems on board to a living analytics layer on shore. Starting from the ship's own schematics, we identify the data that matters, build the pipeline that carries it from vessel to cloud, and construct a business intelligence layer built around the questions you most need answered. One ship, end to end, as a working proof of what the same approach delivers across a fleet.
The underlying twin is the same rigorous foundation every time — schematics, sensor and data-point identification, a pipeline to the cloud. What sits on top is shaped entirely by what you're trying to understand. We define those priority questions together at kickoff and build the BI layer to answer them.
Map the vessel's relevant systems from its own technical drawings.
Determine which data points matter for the questions you've chosen.
Build the path that carries data reliably from vessel to cloud.
Turn that data into a clear, interactive view your team can act on.
One vessel proves the model; the fleet is where the value compounds. The same foundation extends ship by ship, and the BI layer grows with you — new sensors, new data sources and new questions integrate without rebuilding. From a descriptive twin, the path leads naturally to prediction and optimization across the entire fleet.
Both pilots begin the same way: a short scoping conversation to choose the workflow or the vessel, and to agree on what success looks like before any work begins.