Our founder was a key contributor to both the mobile app and website development teams for Maritime Optima, a platform that helps shipping professionals optimize fleet operations. The team implemented tools for route planning, market data analysis, and vessel tracking to improve operational efficiency and decision-making.
Providing real-time maritime data and analytics to enhance decision-making in shipping operations.
Developed AI-driven tools integrated with Microsoft 365 for seamless maritime intelligence.
Mobile app development
Website development
Route planning tools
Market data analysis integration
Vessel tracking functionality
Operational efficiency tools
Integrating multiple data sources to provide accurate, real-time vessel tracking and route information.
Creating consistent experiences across both mobile app and web platforms while maintaining feature parity.
Developing intuitive interfaces to display complex maritime data in an easily understandable format for users.
Implementing robust offline capabilities for maritime professionals operating in areas with limited connectivity.
Established parallel development teams for mobile and web platforms with synchronized feature roadmaps and shared component libraries.
Worked closely with shipping professionals to understand operational workflows and optimize route planning and vessel tracking features.
Implemented advanced data processing pipelines to handle real-time vessel data, market analytics, and predictive routing algorithms.
Conducted regular usability testing with maritime professionals to continuously improve interface clarity and operational efficiency.
Maritime Optima provides ship tracking, route planning and market intelligence to shipping professionals through its ShipIntel web platform and ShipAtlas mobile app. The system is a cloud-hosted SaaS built around a continuous vessel-position ingestion pipeline, a geospatial data store and a shared React and React Native front end that renders everything on Mapbox, with AI tools and Microsoft 365 integration layered on top. A streaming-plus-geospatial shape fit a product whose core value is knowing where every vessel is now and predicting where it will be.
A React web platform for company users and a React Native mobile app share TypeScript components and render on Mapbox.
A gateway serves REST queries and pushes live vessel updates to connected clients over a realtime channel.
Domain services turn raw positions into fleets, routes, port calls and market views that teams act on.
Terrestrial and satellite AIS feeds stream through an ingestion pipeline into a geospatial store that keeps both live and historical ship movements.
Machine learning on historical movements powers predictions and route suggestions, and Microsoft 365 brings the data into the tools teams already use.
Containerised services run in a cloud region with autoscaling ingestion workers and CI/CD for web and mobile releases.
AIS messages from terrestrial receivers and satellites arrive continuously and are normalised, deduplicated and matched to vessels.
Cleaned positions land in the geospatial store and the historical archive, and changed vessels are pushed to subscribed clients.
A user opens a fleet in the web or mobile app; Mapbox renders vector tiles while the API returns current positions and voyage details.
The route service simulates a sea route between ports and computes distance, ETA and alternatives from historical movement patterns.
Prediction models estimate destinations and arrival times for tracked vessels and raise alerts when status or position changes matter.
Alerts flow to Microsoft Teams, and documents linked to a vessel or port open from SharePoint or OneDrive inside the platform.
The mobile app caches fleets and map areas so professionals at sea or in ports with poor connectivity can keep working offline.
Vessel positions arrive as a never-ending stream and are queried by location and time. Separating ingestion workers from a geospatial store let the platform absorb bursts while keeping map queries fast.
The map is the product on both web and mobile. Standardising on Mapbox and a shared TypeScript component library gave feature parity across platforms without two rendering stacks.
Years of AIS history are the training data for ETA and destination models. Treating the archive as a first-class store, not a log, made AI features a natural extension rather than a bolt-on.
Shipping teams live in Teams, Outlook and SharePoint. Meeting them there with Entra single sign-on and linked files lowered adoption friction more than building a separate collaboration suite would have.
“The development team's expertise significantly enhanced our platform's capabilities.”
We ship MVPs, AI agents, and production systems in 8 weeks. Bring the rough spec — we'll scope the build inside a week with a fixed timeline and quote.
