Weather Data Science
- Company typePrivate
- Founded2021
- HeadquartersTokyo, Japan
- Headcount—
- GTM typeB2B
- OfferingServices
Weather Data Science firmographics
Firmographics- Name
- Weather Data Science
- Legal name
- Weather Data Science 合同会社
- Website
- https://weatherdatascience.tokyo
- Company type
- Private
- Founded year
- 2021
- Operating status
- Operating
- Ownership category
- akta.pro rank
Where Weather Data Science is headquartered
LocationHeadquarters
- HQ city
- Tokyo
- HQ country
- Japan
- HQ region
- Asia
Offices1 record
Markets served
Weather Data Science business model
Business model- GTM type
- B2B
- Offering type
- Services
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Operations, Infrastructure
Revenue model
- PV Forecast Self Workshop (PV予測セルフ工房) subscription: Recurring monthly SaaS subscription billed per 予測単位 (prediction unit) at 5,000 JPY/month per unit (tax excluded), with monthly fee = maximum active prediction units in the calendar month × 5,000 JPY. No proration; credit-card-only via Stripe. Customer self-configures prediction settings.
- Bespoke weather-data AI development and consulting (顧問気象予報士): Custom commissioned AI / data-analysis projects for enterprise clients (e.g., NHK fading AI, Rain Tech advisory), typically project-based contracts. Also encompasses ongoing advisory engagements (顧問気象予報士 / Consulting Meteorologist) for weather-affected businesses that need ongoing meteorological guidance without hiring in-house staff.
- Speaking, lecturing and curriculum fees: Revenue from paid and pro-bono lectures (e.g., IAデザイン戦略研究会 webinar, 航空気象研究会 presentations), corporate training sessions, and curriculum development work — including the 気象データアナリスト training curriculum co-developed with DataMix for JMA/WXBC.
- Free 太陽光発電予報 (PV Forecast) web service: Free public solar PV forecast web service launched in November 2022. Serves primarily as a marketing/awareness funnel driving inbound leads to the paid PV Forecast Self Workshop subscription product and bespoke consulting.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Subscription | Monthly | PV Forecast Self Workshop: 5,000 JPY/month (tax excluded) per active prediction unit |
| Freemium | Pay-as-you-go | 太陽光発電予報 free public web service |
| Other | Multi-year contract | Bespoke consulting / AI development — quote-based, not publicly disclosed |
Go-to-market motion4 records
Distribution channels4 records
Marketing channels10 records
Weather Data Science product offering
Product offeringCore offering
Weather Data Science provides weather-data-driven AI development, custom big-data analytics, and a self-service solar PV forecasting SaaS to weather-affected businesses. Its offerings combine a packaged subscription product (PV Forecast Self Workshop) with bespoke consulting (Weather × AI Development, Consulting Meteorologist) and an individual consumer consultation tier. The firm translates JMA numerical forecast GPV data and probabilistic weather predictions into operational decisions for renewable energy operators, broadcasters, aviation, and disaster-prevention clients.
Product overview
Weather Data Science 合同会社 (Weather Data Science LLC), based in Tokyo, is a two-person weather × data science × AI consultancy offering a portfolio that combines a packaged SaaS product, an open-source developer tool, and bespoke professional services. The packaged product layer centers on 太陽光発電予報 (Solar Power Generation Forecast) — a free public forecasting website registered as Japanese Design No. 1740452 — and its successor PV予測セルフ工房 (PV Forecast Self Workshop), a self-service cloud SaaS launching June 21, 2026 that delivers 30-minute interval, up-to-10-day-ahead solar forecasts via web download or API, priced per forecast unit. The developer-tool layer is wxparams, an open-source Python module for meteorological parameter computation hosted on GitHub. The professional-services layer comprises 気象×AI開発 (custom weather-AI development, e.g., NHK fading-prediction AI and Narita Airport fog-prediction AI), 気象×ビッグデータ分析 (custom weather-data analytics), 顧問気象予報士 (embedded meteorologist consulting), and 個人向け気象相談 (individual weather consultations). A supplementary public reference tool, 数値予報GPVタイムライン, supports operational planning with JMA numerical forecast products. Together the offerings pair a self-serve productized forecast service with consultant-led AI and analytics work targeted at industries affected by weather.
Differentiator
Problem solved
Functional benefit
Brands
- 太陽光発電予報 (Solar Power Generation Forecast): A free public solar power generation forecasting web service offered at pvyoho.weatherdatascience.tokyo. The site design is registered as Design Registration No. 1740452.
- PV予測セルフ工房 (PV Forecast Self Workshop)
Products and services
- PV予測セルフ工房 (PV Forecast Self Workshop) Self-serve cloud SaaS for solar power generation forecasting, allowing customers to register facility specifications and receive 30-minute interval forecasts up to 10 days ahead via web download or API. Targeted at solar PV plant operators and developers in Japan needing imbalance-risk reduction, electricity-market bidding, and BG aggregation without hiring in-house meteorologists.
- 太陽光発電予報 (Solar Power Generation Forecast) Free public web service providing solar power generation forecasts (30-min kWh) using JMA numerical forecast GPV data inputs and the company's predictive model. Acts as a marketing and awareness funnel driving inbound leads to the paid PV Forecast Self Workshop subscription product and bespoke consulting. The site design is registered as Japanese Design Registration No. 1740452.
- wxparams (Python Meteorological Parameters Module) Open-source Python module that computes various meteorological parameters from basic weather variables (e.g., dew point temperature from temperature and relative humidity). Distributed via GitHub under the maintainer handle Yoshiki443, with documentation on Qiita and usage examples on note.com. Targets developers and data scientists working with weather data.
- 気象×AI開発 (Weather × AI Development) Bespoke AI development service producing proprietary, client-specific weather-AI models rather than packaged software. Includes commissioned projects such as NHK's fading-prediction AI (contracted 2020-08-03, completed 2023) and AI-based Narita Airport fog prediction. Targeted at enterprises, broadcasters, and government organizations with unique weather-data problems too domain-specific for off-the-shelf products.
- 気象×ビッグデータ分析 (Weather × Big Data Analysis) Custom weather-aware big data analytics and consulting service including ad-hoc meteorologist support such as electricity demand prediction guidance and demand-response / dynamic-pricing-related analytics. Lectures and seminar delivery are part of this offering. Targeted at weather-affected businesses needing data-driven analytics on operational weather data.
- 顧問気象予報士 (Consulting Meteorologist) On-demand meteorologist advisory service addressing one-off weather-data questions, projects too small for a contracted weather company, and support for launching weather-data-driven new businesses. Provides outsourced meteorologist expertise without requiring in-house hiring or full-scale weather company contracts. Targeted at SMBs and startups with ongoing weather-affected operations such as disaster-prevention startup Rain Tech.
- 個人向け気象相談 (Individual Weather Consultation) B2C weather consultation service for individuals and small-scale weather needs. Sits alongside the B2B 顧問気象予報士 service, capturing small consumer weather needs in the consumer market.
Quantifiable outcome
- ~5% annual revenue uplift in wind-power electricity-market bidding PoC via uncertainty-management simulation
- +2 more outcomes
Companies that use Weather Data Science
Customer profileNamed customers7 records
Segments5 records
Ideal customer profiles3 records
Weather Data Science technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration1 record
AI capability7 records
Feature8 records
Weather Data Science partnerships and signals
Strategic signalPartnerships
Twelve partnerships are on record, tiered renewable-energy co-creation partner, industry consortium, flagship advisory client, industry association speaker invitation, case-study reference customer, one-off prestige engagement, curriculum / training co-development partner, flagship enterprise client, channel partner for disaster-prevention business, event-host partner for crowdfunding-era outreach and media partnership via energyshift live event.
- 株式会社エスエナジー (S Energy)renewable-energy co-creation partnerCo-presented at WXBC's 新規気象ビジネス創出ワーキンググループ meeting; their co-creation was selected as the sixth case study in WXBC's 「気象データ活用事例インタビュー」 series.
- 気象ビジネス推進コンソーシアム (WXBC)industry consortiumWDS actively engages with WXBC as a speaker at multiple 気象ビジネスフォーラム events, panel participant in WXBC working groups, and featured partner in WXBC's case-study interview series. WXBC's renewed website features WDS as a case-study subject (https://www.wxbc.jp/memberserviceintroduction/weatherdatascience/).
- Rain Tech (レインテック / RainTech Inc.)flagship advisory clientOngoing 顧問気象予報士 (Consulting Meteorologist) engagement providing technical support and regular meetings to help the disaster-prevention startup build weather-data-driven products. Featured on TV Tokyo WBS broadcast on 2024-01-17.
- 太陽光発電協会 (JPEA)industry association speaker invitationJPEA invited WDS to deliver a web lecture on solar PV output forecast accuracy evaluation at the JPEA open seminar in October 2023.
- wash-plus (株式会社wash-plus)case-study reference customerFeatured as the first case study in WXBC's 「気象データ活用事例インタビュー」 series for a co-creation project applying weather data to wash-plus's laundry business.
- カクイチ (株式会社カクイチ) / IAデザイン戦略研究会industry association speaker invitationIAデザイン戦略研究会 (hosted by Kakuichi) invited WDS as web-lecture speaker on 『気象予報士が提案する、ビジネスにおける気象予測の不確実性マネジメント』; the session sold out.
- NHK 連続テレビ小説制作チーム (NHK Asadora 『おかえりモネ』 production)one-off prestige engagementWDS provided 台本考証 (script supervision) for NHK's morning drama series 『おかえりモネ』 (2021), a story centered on a meteorologist character. Preparation and execution spanned about one year.
- DataMix (株式会社データミックス)curriculum / training co-development partnerJointly developing the curriculum and teaching materials for the JMA/WXBC-certified 気象データアナリスト (Weather Data Analyst) training program since 2020. WDS serves as course instructor; 3 first-cohort certified Weather Data Analysts graduated in April 2022.
- NHK (Japan Broadcasting Corporation / 日本放送協会)flagship enterprise clientNHK commissioned WDS to develop an AI for predicting fading (フェージング) — variation in TV broadcast signal reception caused by weather conditions. The project, contracted in August 2020, was completed with WDS contributing to advanced patent-related content. NHK publicly praised WDS for delivering meteorologically-grounded expertise with surprising speed.
- アルドセイフティ (Aldo Safety / アルドセイフティ株式会社)channel partner for disaster-prevention businessWDS supports Aldo Safety's business launch as a partner and jointly develops the 「あなたの防災」 disaster-prevention service offering that uses weather data to mitigate preventable harm.
- afterFIT (株式会社アフターフィット)event-host partner for crowdfunding-era outreachafterFIT hosted EnergyShift LIVE#7 where WDS pitched its crowdfunding solar PV forecast project and connected with prospective enterprise and partner customers.
- EnergyShift (メディア)media partnership via energyshift live eventWDS was featured in EnergyShift LIVE#7 (hosted at afterFIT) where it presented its solar PV forecast crowdfunding project, gaining exposure across the energy media ecosystem.
Scale indicators7 records
Recent moves7 records
Expansion highlights5 records
Weather Data Science competitors and assessment
Company assessmentEmerging players
- Reask: Probabilistic weather-risk analytics firm focused on tropical-cyclone and renewable-energy forecasting using AI and probabilistic methods. Highly comparable methodology (probabilistic/uncertainty-aware forecasting applied to wind/solar) but more narrowly focused on catastrophe and energy-market risk.
Broad incumbents
- DTN: US-based operational weather-data and analytics provider for agriculture, energy, and transportation, including renewable-energy forecasting. Comparable in serving weather-affected enterprises (especially energy), though primarily in the US market and at significantly larger scale.
- Weathernews Inc. Japan-headquartered global weather-data and forecasting company with broad consumer, enterprise, and media offerings; co-founder Yoshiki is a former Weathernews employee. Weathernews is the most directly comparable commercial weather-data provider in Japan but operates at vastly larger scale across many verticals.
- StormGeo (now part of StormGeo / Alfa Laval portfolio): Global weather-intelligence platform serving shipping, energy, aviation, and media with forecasting and decision-support tools. Comparable to WDS's bespoke weather-AI work in energy and aviation, but at a much larger enterprise scale with packaged SaaS products.
- IBM Environmental Intelligence Suite (formerly The Weather Company): IBM's enterprise weather and climate-data platform serving energy, utilities, and media. Comparable to WDS's bespoke AI/forecasting-for-enterprise work but as part of a much larger software portfolio; represents the kind of full-stack incumbent that large enterprises may default to.
Direct peers
- Tomorrow.io: Weather-intelligence and forecasting-AI platform targeting enterprise verticals including energy, aviation, and on-demand logistics. Most comparable global peer to WDS's PV/wind forecasting and uncertainty-management approach, with a SaaS model and a similar emphasis on operational decisioning rather than raw forecasts.
- Solargis: Global solar-resource and PV-output forecasting data provider serving utility-scale solar developers, operators, and financial institutions. Closest international comparable to WDS's PV Forecast Self Workshop product, with a similar focus on solar forecasting accuracy and operational decisioning.
- Nippon Kishou (日本気象): Established Japanese weather-data services company providing forecasts, environmental monitoring, and consulting to enterprise and government clients. Directly comparable as a Japan-based weather-data services firm serving enterprise customers, though larger and more generalist than WDS's renewable-energy focus.
Others
- WNI (Weathernews) more specifically - retained; add: JMA-affiliated spinouts and university weather-data startups (e.g., 東京大学気候システム研究院系 ventures): Academic and research-organization-affiliated weather-data initiatives (e.g., University of Tokyo AORI, JMA-related research) function as adjacent enablers in the Japanese weather-AI ecosystem. Comparable as enablers of the meteorological-data pipeline WDS builds on, but not direct commercial competitors.
Regional players
- いであ (IDEA Consultants): Japan-based environmental and weather/water-consulting firm serving government and infrastructure clients with meteorological expertise. Comparable as a Japan-based meteorological consulting peer, though focused on environmental/water-resources rather than renewable-energy forecasting.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat4 records
Key risks6 records
Key highlights7 records
Customer concentration
Weather Data Science social profiles
Digital presenceWeather Data Science compliance and trust
Trust signalCompliance2 records
Weather Data Science financial estimates
Financial estimateRevenue estimate
Valuation estimate
Weather Data Science leadership team
Management profileNumber of profiles
Profiles2 records
Weather Data Science funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Weather Data Science M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Weather Data Science
What does Weather Data Science do?
Weather Data Science provides weather-data-driven AI development, custom big-data analytics, and a self-service solar PV forecasting SaaS to weather-affected businesses. Its offerings combine a packaged subscription product (PV Forecast Self Workshop) with bespoke consulting (Weather × AI Development, Consulting Meteorologist) and an individual consumer consultation tier. The firm translates JMA numerical forecast GPV data and probabilistic weather predictions into operational decisions for renewable energy operators, broadcasters, aviation, and disaster-prevention clients.
Is Weather Data Science a public or private company?
Weather Data Science is a private company. It is classified as founder individual operated bootstrapped and is currently operating.
When was Weather Data Science founded?
Weather Data Science was founded in 2021.
Where is Weather Data Science based?
Weather Data Science is headquartered in Tokyo, Japan, in the Asia region.
How does Weather Data Science make money?
Four revenue lines are on record. PV Forecast Self Workshop (PV予測セルフ工房) subscription is the primary driver. The others are bespoke weather-data AI development and consulting (顧問気象予報士), speaking, lecturing and curriculum fees and free 太陽光発電予報 (PV Forecast) web service.
Who are Weather Data Science's main competitors?
Reask is listed as an emerging player. Broad incumbents are DTN, Weathernews Inc., StormGeo (now part of StormGeo / Alfa Laval portfolio) and IBM Environmental Intelligence Suite (formerly The Weather Company). Direct peers are Tomorrow.io, Solargis and Nippon Kishou (日本気象). WNI (Weathernews) more specifically - retained; add: JMA-affiliated spinouts and university weather-data startups (e.g., 東京大学気候システム研究院系 ventures) is listed as an others. いであ (IDEA Consultants) is listed as a regional player.
Does Weather Data Science have an API?
Yes. The PV予測セルフ工房 (PV Forecast Self Workshop) cloud service allows customers to receive forecast values either by download from the service site's My Page or by API. The API provides access to calculated solar power generation forecast values (kWh/30min) at 30-minute intervals. Usage terms restrict reselling, redistribution, or secondary provision of forecast values to third parties, and use aimed at providing the API itself to others is prohibited. No public documentation URL, SDK, authentication method, rate limits, or sandbox information is disclosed.