Forecast interface
Map, forecast screens, charts, selected areas, and clear states for everyday use.
jua.ai
jua.ai builds products on top of weather models. We helped turn a strong technical foundation into the first working web version: an interface where users choose an area on a map, read a forecast, compare signals, and set alerts without relying on internal tools. We worked directly with founder Marvin Gabler. The result was a product that looked and behaved like a real first version, not an internal prototype. It helped jua.ai move toward first customers and supported the story around a funding round of about $2.5M.
~$2.5M round supported by the early version
MVP first usable web version
AWS infrastructure for customer access
Challenge
A strong model needs a clear interface
jua.ai had a serious technical foundation. But users judge the product by how quickly they understand it: which area they are looking at, what the forecast says, where the signals change, and which alerts they can configure.
The job was clarity. The map, charts, states, alerts, access, and infrastructure needed to work as one product.
- Clear area selection and forecast exploration on a map.
- Charts and states that make the data easier to understand quickly.
- Alerts, login, and customer access so the product could move beyond internal use.
Solution
A web product for forecasts and alerts
We built the first version as one product, not a set of technical pages. Maps, forecasts, charts, and alerts had to feel connected and guide the user without extra explanation. A user could choose an area, read the forecast, understand the movement, and set monitoring in the same interface.
Behind that simplicity was the heavy product work: API integration, auth, customer access, notifications, deployment, and AWS infrastructure.
Alerts
Condition setup, statuses, and monitoring flows that connect forecasts to action.
Access
Login, customer keys, limits, and API access for controlled product usage.
Infrastructure
AWS, API Gateway, notifications, Docker, GitHub Actions, and a release process for a product that could keep growing.
Technical work
The interface and the system behind it
The hardest part was making a live technical system feel simple from the outside. Forecast APIs, map behavior, chart data, alert logic, authentication, and deployment all had to line up. When one layer works separately, the product quickly becomes heavy.
We helped connect those parts into the first product foundation: web app, forecast integration, alerts, auth, controlled access, AWS deployment, and a clear release process.
Web product for forecasts, maps, charts, and alerts.
Forecast API integration with interface states and selected areas.
Auth, customer keys, usage limits, and controlled access.
AWS Lambda, API Gateway, Docker, notifications, and GitHub Actions.
QA and release process for fast iteration with the jua.ai team.
Web productForecast APIsMapboxAlertsAuthNotificationsAWS LambdaAPI GatewayDockerGitHub Actions
What changed
The product became clearer
Forecasts, map, charts, and alerts started to feel like one interface instead of separate technical parts.
Customer access arrived earlier
Login, API access, alerts, and infrastructure gave jua.ai a more direct path from internal development to real use.
The early version supported the next stage
jua.ai moved from technical promise to a product people could see and use. This supported the company on the way to a funding round of about $2.5M.
Tell us what you're building
Start with a few detailsWe reply within one business day. Then Azamat joins every first call personally, so you get an honest scope, budget, and fit from the person responsible for delivery.