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WE RADIATE

Location tagging to help operators track their device

SaaS

Web Dashboard

Core Features

MY ROLE

As the sole designer, I collaborated with the founders to define a new direction for the tool

TEAM

PM, Data Analyst, Engineers

DURATION

3 months

IMPACT

User Efficiency and Boost in WeRadiate's Clientele

40%

Reduction in farmer workload

Increase in the Number of Clients

+30%

Increase in the Compost Quality

TEAM

PM, Data Analyst, Engineers

TIMELINE

6 months

TOOLS

Figma, Claude

IMPACT

Faster access to insights and Boost in WeRadiate's Clientele

MY ROLE

I led the new feature from inception, research, testing and adoption.

Resulting in…

40%

Reduction in farmer
workload

Increase in the Number
of Clients

+30%

Increase in the
Farmer's Compost Quality

Jump to the Solution

CONTEXT

Site operators have to manage 15+ sensors in large compost fields

Facilities were using physical flags to mark sensor locations across compost piles.

PROBLEMS WITH THE EXISTING DASHBOARD

Operators were spending significant time locating the right pile & exact placement

“I once spent 40 minutes trying to find the exact section of a compost pile that needed attention..”

-John.R, Site Operator

Resulting in…

Time Lost

Errors Doubled

Poor Quality

CONSTRAINTS

The solution had to work with what was already in the ground

One feature had to solve three constraints at once

Accessibility for non-technical users

Tech Constraints

Avoiding costly hardware upgrades

APPROACH

Exploring low-cost implementation paths & learning trade-offs early

I collaborated with our engineers to understand the best way to implement location mapping without compromising on the supportive experience

Built a rapid prototype in Lovable to pitch a map module as a dashboard addition

I started to build a simple design system to streamline the development of the core product features and allow for consistency across the platform.

Showing rather than describing got alignment faster

OUTCOME

Creating a consolidated map view of all devices

A single source of truth for all site-operators and farmers for timely interventions

Ship pre-configured QR code stickers

Easy for existing clients to self-apply them in the field.

Self tagging devices to

Users scan QR codes to assign each device a location name within their pile

Easy segregation of Devices by Pile

Clear split between device and data

Designing for two points of entry

Easy for existing clients to self-apply them in the field.

Pre-added QR codes - New clients add devices and assign locations during setup.

Existing clients tag their already-deployed sensors by adding + scanning the QR sticker in the field.

PREPPING FOR EDGE CASE

Designed for the person most likely to struggle, not the average user

Easy for existing clients to self-apply them in the field.

Progressive Disclosure

Prepping for mistakes

Feedback Loops

The goal wasn't to avoid failure; it was to make failure recoverable without calling support.

Using AI to pressure test scenarios and expose error states - GPS signal loss, app errors, incorrect QR placement.

RESULTS

Measured against three criterias that matter in the field

Validated through early user testing — watching operators complete the full physical flow without guidance.

40m -> 3m

Decision time to map trends

60% Lesser

Compost reprocessing cost

56% Fewer

Manual sensor + Pile check-ins

PROCESS

Working directly with the founders was a highly collaborative and feedback oriented process.

We went through multiple wireframes, renditions and flows to narrow down on what works best

10+ Card Design Alternatives

20+ Wireframe explorations

(RESEARCH)

1:1 User Interviews - On site Visits

Value Mapping

Usability Testing

1:1 User Interviews - On site Visits

Value Mapping

Usability Testing

1:1 User Interviews - On site Visits

Value Mapping

Usability Testing

Goal setting workshops with users

Building comprehensive research docs

(COLLABORATIONS)

Engineers

Soil Analysts

AI Tools (Claude)

Engineers

Soil Analysts

AI Tools (Claude)

Engineers

Soil Analysts

AI Tools (Claude)

Exploring types of data visualizations

Benchmarking with Eng + Analysts to define tokens

LEARNING AND TAKEAWAYS

Build first, iterate fast

Working in a startups means not waiting to build the perfect product. It is to build, test, and iterate to be able to get feedback and improve the product as we go.

Embracing Ambiguity

Advocating for Design Decisions

The Power of Feedback

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