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DIVIROD RAISES NEARLY $2M TO COLLECT WATER LEVEL DATA

The startup measures water levels by decoding the reflections of satellite
signals off of the water.
Written by Jeff Rumage
March 4, 2022Updated: March 9, 2022


A Divirod sensor detects the reflection of satellite signals on a dam near
Madrid. | Photo: Divirod

The founders behind Boulder-based Divirod are on a mission to compile
highly-accurate, real-time water data that could help monitor local water
supplies, warn against flooding and prevent boats from getting stuck in shallow
water.

After raising $1 million in funding last year, co-founder Adam Wilson told Built
In the company recently raised nearly $2 million from TDK Ventures. Wilson said
the company used the funding to double its headcount from six to 12 employees.

Existing water monitoring sources are outdated, sparse and disparate, according
to Divirod co-founder and CEO Javier Marti.

Marti previously worked at the European Space Agency, where he used satellite
technology to measure sea levels. After realizing a gap in the market, Marti
joined with Wilson to form Divirod, the first company to measure water levels to
the nearest millimeter by sensing the reflections of satellite signals bouncing
off the water.

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Divirod can install the sensors within 20 minutes using poles that it situates
in the ground or nearby buildings. The sensors and can pick up the reflections
of satellite signals bouncing off water within a 10-acre area.

The company’s cloud-based, machine-learning software decodes those signals to
generate hydrological models and 3D maps of the surfaces of water, snow or soil
moisture content. The data is then sent to clients under a data-as-a-service
business model.

Divirod’s data is currently being used to measure municipal water reservoirs and
other bodies of water. It is also used to ensure the water levels at ports,
marinas and harbors are high enough to prevent boats from getting stuck.

The sensors are also installed on the roofs of tall buildings to make sure snow
and water don’t cause drainage issues, damage to equipment or a collapsed roof.

“We’re challenging the status quo of how water is being monitored as a risk.
It’s risky when we run out of water or have too much water,” Wilson said. “I
think this is one of the most important datasets that could exist.” 

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