Introducing SeaLegs AI for Developers!

SeaLegs AI — Wed, 11 Feb 2026 00:44:34 +0000

We're thrilled to announce the public launch of the SeaLegs API - a developer-friendly way to integrate AI-powered marine weather forecasts into your applications. Whether you're building a sailing app, marina management system, or any tool that helps people enjoy the water, SeaLegs gives you the data you need.

What's in the API?

The SeaLegs API provides comprehensive marine weather data through a simple REST interface. Here's what you can access:

7-Day Forecasts - Detailed hourly and daily forecasts including wind, waves, temperature, and precipitation.
AI Classifications - Smart daily ratings that tell you at a glance whether conditions are good for boating.
Global Coverage - Forecasts for coastal waters, lakes, and offshore locations worldwide — from Florida to the Mediterranean to Australia.
Multi-Model Data - Synthesized predictions from leading weather models for improved accuracy.

Quick Start

Getting started is easy. First, create your developer account to get an API key. Then make your first request:

curl -X GET "https://api.sealegs.ai/v1/forecast" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d "lat=25.7617" \
  -d "lon=-80.1918"
You'll receive a JSON response with detailed forecast data:

{
  "location": {
    "lat": 25.7617,
    "lon": -80.1918,
    "name": "Miami, FL"
  },
  "daily": [
    {
      "date": "2025-11-20",
      "classification": "good",
      "confidence": 0.87,
      "wind_speed_avg": 12,
      "wave_height_avg": 2.1,
      "summary": "Light winds and moderate seas..."
    }
  ],
  "hourly": [...]
}

Pricing That Scales With You

We designed our pricing to work for projects of all sizes:

Pay-as-you-go - Start at just $10 for 200 forecast-day credits
No monthly minimums - Only pay for what you use
Volume discounts - Better rates as your usage grows
Enterprise plans - Custom solutions for high-volume applications

A "forecast-day" is one day of forecast data for one location. So a 7-day forecast uses 7 credits. This simple model makes it easy to predict your costs.

Documentation & Support

We've invested heavily in making SeaLegs easy to integrate:

Comprehensive docs - Detailed API reference with examples in multiple languages
Quickstart guides - Get up and running in minutes
Interactive console - Test API calls directly from your browser
Email support - Real humans ready to help when you need it

Embeddable Widgets

Don't want to build your own UI? We also offer embeddable SpotCast widgets that you can drop into any website with a single line of code. Display beautiful, responsive marine forecasts without writing any custom frontend code.

What's Next

This launch is just the beginning. Here's what's on our roadmap:

Webhooks - Get notified when conditions change
Historical data - Access past forecasts and observations
Custom alerts - Set thresholds for specific conditions
More widget styles - Additional visualization options

We're building SeaLegs in close collaboration with our developer community. Have a feature request? We'd love to hear it.

Get Started Today

Ready to bring marine weather intelligence to your application? Here's how to get started:

Create your free developer account
Get your API key from the dashboard
Follow our quickstart guide
Start building!

We can't wait to see what you create. Welcome to SeaLegs AI for Developers!

- The SeaLegs AI Team
developer.sealegs.ai
www.sealegs.ai

Reading Weather Charts Is So 2025

SeaLegs AI — Tue, 10 Feb 2026 01:23:56 +0000

Open your favorite marine weather app. What do you see? A colorful wind map. A spaghetti plot of wave models. A pressure chart with isobars that mean nothing to 95% of boaters. Maybe a GRIB viewer if you're feeling adventurous.

Now ask yourself: does your user actually know what any of that means?

Most marine weather tools — from consumer apps to developer APIs — are essentially doing the same thing they did a decade ago: pulling raw weather model output and painting it on a map. The visualization has gotten prettier, but the fundamental problem hasn't changed. They're showing you the data and hoping you know what to do with it.

The Weather Chart Industrial Complex

Here's how most marine weather services work today:

Ingest raw data from weather models (GFS, ECMWF, ICON, etc.)
Render that data as charts, maps, or tables
Let the user figure out whether it's a good day to go boating

That last step is doing a lot of heavy lifting. Interpreting a marine forecast requires understanding how wind speed interacts with wave period, how fetch affects sea state, what a backing wind means for afternoon conditions, and how your specific vessel handles different sea states. It's a skill that takes years to develop.

And yet, almost every marine weather service assumes you already have it.

Look at the tools boaters and developers rely on today. Windy gives you gorgeous animated maps of wind, pressure, and wave data — but the user still has to know what a 15-knot northwest wind at a 4-foot swell means for their boat. PredictWind offers GRIB viewers and multi-model comparisons, which is great if you're an offshore navigator but overwhelming if you're planning a weekend fishing trip. Buoyweather displays hourly graphs of wind speed, wave height, and swell direction — useful data, but it's still raw numbers that the user must mentally synthesize into a go/no-go decision. Passage Weather renders GRIB data on charts for offshore planning, and SailFlow shows wind station data and forecasts optimized for wind sports enthusiasts.

These are all legitimate, well-built tools. But they all share the same design assumption: the user is the analyst. They present information and leave the interpretation — the hard part — entirely to the person staring at the screen.

Wind arrows, color-coded wave height maps, multi-model comparison charts — these are tools designed for meteorologists. They're powerful, detailed, and absolutely useless for the family checking whether Saturday's trip to the Keys is a go.

What Developers Keep Building

If you're building a marine app, you've probably been down this road. You find a weather data source, spend weeks parsing GRIB files or wrangling JSON blobs, build some chart components, and ship it. Your weather page looks something like this:

# The old way: download GRIB data, parse it, and...
# hope your users know what it means

import pygrib

grbs = pygrib.open('gfs_wave_model.grb2')

# Extract significant wave height
wave_height = grbs.select(name='Significant height of combined wind waves and swell')[0]
data = wave_height.values  # 2D array of wave heights in meters

# Extract wind speed
wind_u = grbs.select(name='U component of wind')[0].values
wind_v = grbs.select(name='V component of wind')[0].values
wind_speed = (wind_u**2 + wind_v**2)**0.5  # m/s

# Now what? Render a chart and let the user figure it out?
# Is 1.8m at what period? From what direction? For what boat?

You end up with a beautiful visualization of data that most of your users can't interpret. And the ones who can? They already have their own tools. They're not using your app.

The Question Nobody's Asking

Here's the thing: your users don't want weather data. They want an answer to a simple question:

"Should I go out on the water tomorrow?"

That's it. They don't want to know that the GFS model shows 15kt winds from the south-southwest while ECMWF has 12kt from the south, and the wave model shows 4ft at 7 seconds but there's a secondary swell of 2ft at 12 seconds from the east. They want to know if it's going to be a good day, a rough day, or a stay-home day.

A marine weather API should answer that question directly — not hand over raw ingredients and expect your user to be the chef.

What "Good Enough" Actually Looks Like

Compare the GRIB parsing approach to what an AI-powered marine weather API can deliver:

# The new way: ask the API and get an actual answer

import requests

response = requests.post(
    "https://api.sealegs.ai/v3/spotcast",
    headers={"X-API-Key": "your_api_key"},
    json={
        "latitude": 24.5551,
        "longitude": -81.7800,
        "start_date": "2025-12-20",
        "num_days": 3,
        "vessel_info": {
            "type": "center_console",
            "length_ft": 24
        }
    }
)

forecast = response.json()
day = forecast["latest_forecast"]["ai_analysis"]["daily_classifications"][0]

print(day["classification"])  # "GO"
print(day["summary"])
# "Excellent conditions for your 24ft center console. Light east
#  winds 8-10kt with a gentle 2ft swell at 7-second periods.
#  Best window is morning through mid-afternoon before sea
#  breeze fills in around 3pm."

No GRIB parsing. No chart rendering. No expecting your user to be an amateur meteorologist. Just a clear, plain-English assessment that accounts for the vessel type, location, and actual conditions.

The classification field gives you one of three values: GO, CAUTION, or NO-GO. That's the answer your users actually want. The detailed summary provides context for anyone who wants it, but the decision is already made.

But Wait, I Like Charts

Fair point. And we're not saying charts are useless. For professional meteorologists, offshore racing navigators, and weather enthusiasts who genuinely enjoy analyzing model data, charts are invaluable tools. A synoptic chart tells a story that a single classification can't.

But here's the thing: those people are maybe 5% of the boating population. The other 95% — the weekend anglers, the family cruisers, the charter operators trying to make a go/no-go call for tomorrow's trip — don't need a weather chart. They need a weather answer.

If you're building for that 95%, stop making them read charts. Build with an API that does the reading for them.

What This Means for Developers

If you're integrating marine weather into your app, you have a choice:

Option A: Download model data, build a GRIB parser, render charts, and hope your users can interpret them. Budget several months of development time. Handle model updates, data format changes, and visualization bugs forever.
Option B: Call an API that returns GO / CAUTION / NO-GO with a plain-English summary tailored to the user's vessel. Ship in a day. Or embed a widget and ship in five minutes.

Option A gives you maximum control. Option B gives your users what they actually need. For most marine applications — from fishing apps to marina dashboards — the answer is Option B.

The weather data is a means to an end. The end is a decision. The best marine weather API is one that makes the decision easy.

The Shift Is Already Happening

Think about other industries that went through this same transition. Navigation used to mean reading paper charts and plotting courses. Now it means typing an address into Google Maps. Financial analysis used to mean reading ticker tape. Now an app tells you if your portfolio is up or down and why.

Marine weather is next. The raw data isn't going away — it'll always be there for the enthusiasts and professionals who want it. But the default experience is shifting from "here's the data, good luck" to "here's what the data means for you."

If you're building the next marine app, build for where the industry is going, not where it's been. Your users will thank you.

Get Started

Ready to stop shipping weather charts and start shipping weather answers? The SeaLegs API takes about five minutes to set up. You'll get AI-analyzed forecasts for any location on Earth, customized for your user's vessel, in a single API call.

Reading weather charts is so 2025. Your app should be smarter than that.

DEV Community: SeaLegs AI