Taara, a Google moonshot organization, builds free-space optical communication links that beam internet connectivity using light. When traditional fiber can't reach, for example across rivers, through dense cities, or remote areas, Taara's Lightbridge closes the gap, But, before deploying, operators need to know if a link will actually work. It needs clear line of sight and high reliability, which is dependent on visibility. Taara Link Planner is the web-based tool to answer the question, using historical weather data, terrain analysis, and line-of-sight modeling to predict availability before anyone climbs a tower.
Discovery started with researching wireless optical communication, how light-based connectivity is different from RF and how weather affects visibility. I spent considerable time with the Taara modeling team and researchers to better understand how they generate predictions. Most importantly I interviewed network engineers and planners to understand how they assess link feasibility and link budgets. I also conducted site visits with field installers to observe physical site surveys and deployments.
Network engineers and planners need a way to evaluate the feasibility and predicted performance of free-space optical links before deployment, so that they can make confident infrastructure decisions and build networks that reliably deliver connectiity.
Network engineers/planners emerged as the primary user early in discovery. These are the people evakuating whether a link will work, and if it supports their network, before anything gets deployed. They will run feasibility checks, compare candidate locations, and build a case for their stakeholders. They're technical and risk-adverse.
We identified the primary workflow involved the network map, where users could place links, open a details container and review line of sight and availability predictions. to provide a progressive disclosure experience, drilling into building and terrain or availability analysis would provide additional data and opportunities to evaluate data details. Users also expressed the need for bulk analysis, a way to upload as many as 10,000 links at once and have the tool assess for clear line of sight and availability. Learning how engineers plan their links and organize projects, we understood the need for links management.
Spending time with users helped us understand the complexities and nuances of the work. Nothing was binary, good or bad, rather it was about design and tradeoffs.
Once the prototype was complete, we launched usability testing. Results were positive with most users finding the platform intuitive and user-friendly. Learnings included the need for additional context, especially with the use of tool tips, to help guide decision making.
The most challenging problem for Taara Link Planner is how to solve the experience for when the tool does not have accurate weather data for the location of the link. It happens fairly frequently outside the US, and Taara has customers all over the globe. When there is not a vetted weather station, or the station is more than 200km from the link location, the model selects a weather twin. Using an LLM, the tool finds a city with identical climate and creates an availability prediction based on this twin location.
The weather twin feature created internal debates, particularly with the Sales team. Fears of customers being confused, not understanding the weather twin experience, or not trusted it became a blocker for the GA release.
To help the Sales team and other stakeholders gain trust in the design and in the tool, we engaged in extensive UAT with network engineers and planners. Fortunately, UAT is successful. On the scale of 1-5 for how likely are you to use this tool to design your network, 1 being not likely and 5 being extremely likely, the average score was a 4.9. The Sales team gained confidence in the tool and GA happened on time,
Link Planner is a self-serve planning tool that lets network engineers evaluate link feasibility. Users place terminals on a map, run availability analysis powered by weather and terrain data, and get a clear picture of whether a link will perform at a given location and range. For data-sparse regions, weather twins provide predictions where local stations don't exist. Bulk analysis lets planners evaluate entire networks at once instead of one link at a time. Every prediction surfaces the data behind it, where it came from, how complete it is, and how confident the user should be, so planners can make successful deployment decisions.