BLOOMCAST item detail: rose forecasts for 1 week, 2 weeks and 1 month with 80% range (demo account)
Price forecasting AI for flowers and produceReal prices × Sentinel-2 × weather

Next week’s flower and vegetable prices, before the market sees them.

BLOOMCAST learns from prices that actually traded: the aT Yangjae flower auction, the Seoul Garak wholesale market and customs import unit values. It adds satellite views of growing regions, weather and the demand calendar (graduations, Parents’ Day, kimchi-making season) to forecast each item 1 week and 1 month ahead with an 80% range.

Rose · 1 wk ▼ expected downGerbera · 1 wk ▲ expected upNapa cabbage · kimjang ▲ D-5Korea ← Colombia carnation · 1 mo ▼ slightly down
57forecast items
33growing regions watched
1 wk · 1 moforecast horizons
2019–price history

The problem

Prices move every day. Buying is still decided by gut feel.

Flower and vegetable prices can swing within a week with weather, harvests in growing regions and holiday demand. Yet the timing and size of purchases still rely on experience.

01

Holidays move flower prices

Auction prices rise and fall around graduations, Parents’ Day and the year end. When you buy decides your margin.

02

Far-away flowers, late signals

For flowers from Colombia, Kenya or the Netherlands, weather and harvest in the growing region take time to show up in prices.

03

Outlooks without numbers

“Prices may rise” is not enough to set contract volumes. You need how much, within what range, and how often the forecast was right.

Real screens

Forecast, range, reasons and accuracy on one screen.

These are real screens from the BLOOMCAST console (demo account).

How it works

The ground truth is the price that actually traded.

Collect real prices

Auction, wholesale and customs prices are pulled daily and monthly from public data and stored as training targets.

Watch growing regions

Fields in main growing regions are read monthly from Sentinel-2 10 m imagery to build a crop supply index, plus MODIS vegetation index and ERA5 weather anomalies.

Train and backtest

Models per horizon learn from price momentum, season, last year’s pattern, holidays and growing-region signals, then are re-run at past dates and scored.

Forecast, alert, report

Median and 80% range per horizon, the drivers that moved the forecast, price alerts and CSV/PDF reports.

Public data with traceable sources

aT flower auctionKAMIS Garak wholesaleUN ComtradeWorld Bank Pink SheetSentinel-2 L2AESA WorldCoverMODIS NDVIERA5 · Open-MeteoECB exchange rates

Accuracy principle

We show the items where the model loses, too.

Every accuracy figure comes from a rolling backtest. At each past date the model is retrained with only the data known then and compared with the price that followed. The baseline is the simplest rule: “the price stays where it is”.

38 / 53

items where the model beats the baseline (72%)

5.7% · 6.3%

median MAPE (chosen method · baseline)

68%

median direction hit rate (moves beyond ±3%)

13 / 53

items helped by satellite or weather signals

16.7%
22%Rose · 1 wk
35.4%
45.2%Gypsophila · 1 wk
25.7%
30.8%Gerbera · 1 wk
10.1%
10.2%Napa cabbage · 1 wk
3.5%
3.3%Onion · 1 wk
2.1%
3.6%Korea ← Colombia carnation · 1 mo
BLOOMCAST model error (MAPE)“Price stays the same” baseline

Figures from the demo screen on 15 Nov 2026, nearest horizon. They differ by item, horizon and date. Where the model does not beat the baseline, the baseline value is used. Items such as onion, where the model is no better, are shown as they are.

Roses and carnations on a florist table with a tablet showing a price forecast chart (illustration)

Who uses it

People who have to buy before prices move.

The same screens support importers and wholesalers, flower retail, food buyers and supply planners.

Why BLOOMCAST

Not “prices may rise”, but a range and a report card.

Price lookup services show past prices. BLOOMCAST shows where prices are heading and how well those forecasts have done.

Experience and gut feelPrice lookup and market notesBLOOMCAST
Time frameNowPast prices1 week and 1 month ahead
UncertaintyNoneUsually none80% forecast range
ReasonsPersonal judgementMarket commentsDrivers behind each forecast
Growing-region signalsRumours and newsUsually noneSatellite and weather, only when they help
Accuracy checkNoneNoneBacktest published per item

General characteristics of each approach. Individual services differ. Full comparison

Pricing

Start with the items you trade.

Starter

KRW 99,000/month
  • 10 watched items
  • 1-week and 1-month forecasts with range
  • Price alerts · CSV
Most popular

Pro

KRW 490,000/month
  • All items · all growing regions
  • PDF reports · backtest detail
  • 5 users · API export

Enterprise

Custom
  • Model trained on your own purchase prices
  • Custom items and growing regions
  • Data integration · SLA

Trial forecast

On request
  • Trial forecast for the items you name
  • Shown next to the baseline
  • Demo console walkthrough

Prices in Korean won per month. Tax and contract terms are explained during consultation.

The company

A team that has run AI in the field.

BLOOMCAST is built by MomentCube, an industrial AI company in Incheon, Korea. We bring our experience of turning field and satellite data into decisions to price forecasting.

3 lead R&D projects

Switchgear predictive maintenance, context-aware AI safety, Safety4Cut with NVIDIA.

3 registered patents

Industrial AI safety, autonomous equipment management, automatic report generation.

Public-sector operation

AI fire watch and safety monitoring at Incheon Environmental Corporation.

Certified venture

Innovation-growth venture, in-house R&D department.

FAQ

Frequently asked questions

What is BLOOMCAST?

BLOOMCAST is a price forecasting service for flowers and farm produce built by MomentCube. It learns from real auction, wholesale and import prices, adds satellite views of growing regions, weather and the demand calendar, and forecasts each item 1 week and 1 month ahead with an 80% range.

Can satellites tell you flower prices?

Only partly, and we say so. Most export flowers grow in greenhouses, so for flowers the demand calendar, recent price movement and sunlight and temperature in the growing region are stronger signals. Satellites are used for open-field crops. For each item we compare backtests with and without the satellite signal and keep it only when error falls by 1% or more. Both numbers are shown on the item screen.

How accurate is it?

It depends on the item and horizon. The accuracy screen publishes backtest error for every item next to the “price stays the same” baseline. One-month forecasts for volatile fresh vegetables are hard; around holidays, the direction of flower prices is easier to call than the level.

Can it learn from our own purchase prices?

Yes. On the Enterprise plan we build a dedicated model that uses your own purchase or auction records as the ground truth.

Which items are covered?

57 items in four markets: Korean flower auction, global flower import prices, Korean produce wholesale and global agricultural commodities. Enterprise customers can add items and growing regions.

Is this investment advice?

No. Forecasts are statistical estimates shown with a range. Use them together with your own judgement.

Get started

Tell us the items you trade.

We reply with a trial forecast for those items, shown next to the simple “price stays the same” baseline, so you can judge it on your own numbers.