Open Instinct: an open-source Instinct. A personal agent you text on iMessage, with its own computer and a trusted network of other agents. Built on Pi, Inkbox, Maritime and Composio.
Open source simulator for maritime robotics researchers
Android AIS receiver for RTL SDR dongles, Airspy R2, Airspy Mini, Airspy HF+ and TCP (RTL-TCP and SpyServer). Output is send via UDP and visualized on the built-in map
Global maritime intelligence platform for real-time vessel tracking, AIS data analysis, sanctions monitoring, shipping routes, port activity, anomaly detection, OSINT analytics, and geospatial insights
OpenBridge design system implemented as Lit-based web components with support for all major frontend frameworks.
Modelling marine traffic in the ice-covered Baltic Sea using AIS data
C++20 offshore crew eligibility, muster station staffing, drill timing and audit core.
RADAR is a real time geospatial intelligence platform that aggregates aircraft, maritime, cyber, OSINT, GPS interference, and threat alert data to provide global situational awareness through an interactive intelligence dashboard
Dataset and Evaluation Scripts for Obstacle Detection via Semantic Segmentation in a Marine Environment
WaSR Segmentation Network for Unmanned Surface Vehicles v0.5
3D multi-domain tactical intelligence map — live ships, flights, satellites, cables & space weather in the browser. Time scrubbing, scenario replay, physics-based anomaly detection.
A python framework to predict trajectories of vessels with machine learning algorithms, such as lstm, seq2seq, etc.
Maritime route optimization system for Merchant Marine. Weather-aware A* routing, Holtrop-Mennen vessel modeling, Copernicus data integration.
API REST pública de tábua de marés do litoral brasileiro, escrita em V com veb. Consultas em JSON sem cadastro, porto mais próximo por geolocalização, SQLite + PostgreSQL, Stripe e rate limit por plano. SDKs em JS/TS, Go e C#.
[NeurIPS 2025 Spotlight] Neptune-X: Active X-to-Maritime Generation for Universal Maritime Object Detection
A PyTorch reimplementation of the WaSR obstacle segmentation model
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