A practical, honest walkthrough of pulling AIS data into Python — what the messages actually contain, where the gotchas live, and how to build something useful in a few dozen lines.
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Maritime email alerts and API-based vessel monitoring look like the same product wearing different clothes. They aren't. Here's what the difference actually costs you.
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A walk through what actually gets recorded when a ship enters a port, why the timestamps are weirder than you think, and how to query the data cleanly without getting burned.
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How to build vessel geofence webhooks that actually fire when you want them to — AIS data quirks, debouncing, idempotency, and the small architectural decisions that separate a useful alert from a n...
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An MMSI looks like a phone number for a ship. It almost is. Here's what really happens when you query one — and how to build a lookup that doesn't lie to you.
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An MMSI feels like a permanent vessel ID. It isn't. Here's what an MMSI actually identifies, why ships accumulate former names like surnames, and what a real vessel lookup API has to do to keep up.
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How we migrated a maritime AIS platform from MongoDB to TimescaleDB, built two-layer spatial indexing with H3 and PostGIS, and found 240 dead struct tags from the old world.
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We process a million AIS messages per hour. Four out of ten are garbage. This is how we built a four-layer filtering pipeline to catch phantom ships, GPS glitches, and spoofed positions.
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