Opportunities › Hyperlocal rain vector prediction for weather apps › Proposed app
Raincourse
Rain direction and speed from radar, as a fast API for weather apps
- Score
- 58
- confidence 46
- Evidence
- 4
- items on the page
- Rivals
- 2
- named in sources
- First version
- 45 d
- estimate
- Type
- Desktop app
- PWA: runs in the browser, installs on Mac and Windows
- Market since
- 2012
- Mature market · AI estimate
ScreensConcept
Desktop app: Weather app developers integrate APIs, test accuracy, and review usage data in a development environment with code and dashboards. Sample screens on a computer, in the proposed brand. Their numbers are sample data.
Rain vector
Updated 40 s agoNE 18 km/h
About this appAI proposal
Raincourse is an API that tells your weather app where rain is heading. Send a location and recent radar frames. You get back the direction and speed of each rain cell, plus the minutes until rain starts or stops at that spot.
It is for mobile and web developers and small weather app teams who want a clear line like 'rain in 12 minutes, moving northeast' without training their own model or paying general-purpose language model prices on every request.
A compact model built for one job, rain movement on radar, sits behind the API. A dashboard lets you replay past storms and compare predicted paths with what happened, so you can judge accuracy in your own region before you ship.
- Tagline
- Tell your users which way the rain is going.
- Voice
- PlainPreciseCalm
- Why this name
- Course means the path something takes. Raincourse names the one thing it does: the path of rain. Two plain words, easy to say.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Rain vector endpoint
One call returns heading, speed and confidence for rain cells around a point, ready to show as an arrow or a sentence.
No member yet
Minutes-to-rain for any point
Get the expected start and stop time of rain at a user's location, as a range instead of a false exact minute.
No member yet
Bring your own radar
Post radar frames from your licensed source or give a tile URL. Raincourse estimates motion; it does not resell radar data.
No member yet
Storm replay and scoring
Replay past events in your region and compare predicted and actual paths. Know the accuracy before you commit.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#12343BDeep Teal · primary#F4F1EAPaper · surface#1B2A33Ink · text#F2A33ASignal Amber · accent#7FB3C8Cloud Blue · data
Typography
Aa
Raincourse
ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
Tell your users which way the rain is going.
PricingAI proposal
The material gives no competitor prices. It says only that large general-purpose models are too costly for this task. These tiers are a starting point to test, not a market-based figure.
Trial
Free
- 5,000 requests a month
- Storm replay on one region
- Community support
Build
$49 a month
- 100,000 requests a month
- Batch requests
- Storm replay and scoring
- Email support
Scale
$249 a month
- 1 million requests a month
- Rain alert webhooks
- Usage alerts per key
- Priority support
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$194,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- Visible inside customers’ products. Free and Build plans show a small 'Rain path by Raincourse' credit beside the forecast line in customers' apps. App users and other developers see the name where the feature is used.
- Do they become customers?
- App users who see the credit are mostly not buyers. Test whether developers at other weather apps follow the credit and sign up, and whether paying plans drop the credit.
- First customers
- Independent developers and teams of one to five building consumer weather apps for one region, such as a single country, who today show only a radar map or basic rain alerts.
- Where to reach them
- Hacker News and Show HN: Post a live demo with a public storm replay where readers can check predicted paths against what happened.
- Weather app developer communities: Offer free trial keys in forums and subreddits for weather app makers, and ask for replay tests on their region.
- Direct outreach: Email small weather app makers a replay of a recent local storm run through Raincourse.
- First milestone
- Five weather app teams in one region run a trial, and at least two move to a paid plan within 60 days.
Why people already pay for this
- Public claimWeather apps have struggled to accurately predict rain movement direction on radar for years
- Public claimDark Sky achieved superior performance with machine learning but has not evolved since acquisition
- Public claimNewer lightweight models offer meaningful accuracy improvements at lower cost and faster speed
- Public claimLightweight AI models unlock weather prediction use cases that were previously blocked by cost and performance constraints
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · Prediction modelCompact motion-prediction model, self-hostedFast, low-cost inference tuned to radar motion is the core of the product.
- This app · Inference computeGPU or CPU inference service with autoscalingVercel functions are not suited to running the model at low latency.
RisksAI inference
- AIA small model may not beat existing approaches across climates and radar types. Accuracy must be proven on held-out storms before any claim is made.
- DataTraining and live use need radar data with licences that allow commercial use. Coverage and terms differ by country and may limit launch regions.
- CommercialLarge weather data providers may add rain movement to their own APIs, and app teams may keep what they have.
- TechnicalRain forecasts must return fast and stay up at peak storm times, when many users open apps at once.
- CommercialEvidence is public claims from forum posts only. Whether developers will pay for this one feature is untested.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.