Context
Saildrone is working on a feature to provide the US Navy with data gathered by its autonomous ocean vehicles.
Challenges
There are no comparable products available for competitive analysis and research. Also, there is limited ability to conduct user testing with US Navy and Coast Guard personnel.
Hypothesis
Implementing design patterns from popular consumer products in Saildrone Mission Portal can decrease the time needed to become proficient.
Wireframes
During the initial wireframing stages, I examined interactions similar to those found in Google Maps and home security cameras.
I collaborated with developers to design and quickly construct the Mission Portal using the Angular framework.
Final Design
Using machine learning, any vessel deemed suspicious will be highlighted at the top of the timeline.
Users can scroll through a timeline, which displays density of maritime traffic.
Additionally, they can select a specific date range to view historical data and traffic details within that period.
The user has the ability to watch a live stream from a Saildrone at sea.
This live view is enhanced with machine learning data and information from the AIS transponder.
Outcome
After successful trials in the Arabian Gulf, the US Navy intends to purchase more units, generating an annual revenue of $150M.
$1M
In Revenue per
Saildrone per Year
150
Saildrones Ordered
by the US Navy
$100M
Raised in Series
C Funding
In Q4 2021, Saildrone secured an additional $100M, bringing their total funding to $190M.
