Join us and be a part of the solution

Help your customers make informed decisions to prevent global warming by integrating our A.I. powered, hyperlocal, near real-time water vapor API.

Alert.

Integrate the water vapor API in your app and give your users a way to be informed of water vapor levels in the atmosphere around them.

Show.

Using near real-time water vapor data, let your users be aware of the water vapor at all times.

Recommend.

Inform your users of the seasonal and locational increase in water vapor and advise them on the preventive steps to take to reduce their contribution to global warming.

Engage.

Providing useful information will not only increase user engagement of your application but also will keep your users hooked.

Choose quality over quantity.

Ambee aggregates water vapor data from multiple sources combining on-ground sensors, satellite imagery and statistical inference to ensure accuracy and availability of the highest order.

Global Coverage

Ample data coverage across the world with new countries being added every week.

Data Accuracy

Data validation is prioritised to ensure accurate data delivery of near the atmospheric water vapor.

Quick Response

When called upon, Ambee's Water Vapor API delivers accurate data quickly for a frictionless and user-friendly experience.

Detailed Report

Ambee's Water vapor API gives a comprehensive and actionable insight with a detailed view into atmospheric water vapor.

Real-Time Data

Raw pollen data is made available in real-time for the user location.

Easy to Integrate

Ambee's water vapor API is developer-friendly and easy to integrate into any program, application or product.

Without the naturally occurring water vapor and CO2, the earth's average temperature would be nearly 35°C (63°F) colder, and the planet would be much less suitable for human life.

Start empowering your audience today with our environmental data for free.

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100 API records/day

Zero limitations on country

Water vapor Data & Humidity

Air pollution & Temperature recommendations

Transparent & logical approach to deriving Pollen data

Ambee’s AI algorithms are based on machine learning and mathematical models. Ambee uses historic data analysis to validate and provide real-time, hyperlocal street level pollen data. We model data based on many factors such as Vegetation Index, Temperature, Wind Speed, Wind Direction, Pollen Seasons.

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Ambee ranks amongst YourStory's 'Top 50 Disruptive Startups' based on the environment intelligence innovation through real-time information and hyperlocal air quality with EPA-benchmarked sensors.

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YourStory

Recognizing Ambee as Top 50 Disruptive Startups in India