A web dashboard that allows users to explore complex datasets using APIs and dynamic map visualizations.
A web dashboard that allows users to explore complex datasets using APIs and dynamic map visualizations.
A web dashboard that allows users to explore complex datasets using APIs and dynamic map visualizations.
When I joined SatSure, I was drawn to the challenge of designing for a geospatial company. SatSure needed a better way for teams and clients to access datasets quickly. The existing tool was clunky and confusing, failing to solve the core problem.
Redesigned this tool from the ground up to enable API access and map visualization. Collaborated closely with engineers and product manager to build core platform features that later became the foundation for company-wide dashboards. Grateful to the team for trusting me with this role in my first 6 months.
Most fulfilling part? Simplifying complex backend data into clear, usable dashboard insights and grateful for the conversations beyond Figma that helped build strong cross-functional partnerships and shape the product meaningfully.
For everyone reading - this case study comes in two flavors:
#1 A crisp, showy product reveal with videos for the quick explorers, and
#2 An in-depth breakdown for those who love digging into the finer details. Get ready :)
When I joined SatSure, I was drawn to the challenge of designing for a geospatial company. SatSure needed a better way for teams and clients to access datasets quickly. The existing tool was clunky and confusing, failing to solve the core problem.
Redesigned this tool from the ground up to enable API access and map visualization. Collaborated closely with engineers and product manager to build core platform features that later became the foundation for company-wide dashboards. Grateful to the team for trusting me with this role in my first 6 months.
Most fulfilling part? Simplifying complex backend data into clear, usable dashboard insights and grateful for the conversations beyond Figma that helped build strong cross-functional partnerships and shape the product meaningfully.
For everyone reading - this case study comes in two flavors:
#1 A crisp, showy product reveal with videos for the quick explorers, and
#2 An in-depth breakdown for those who love digging into the finer details. Get ready :)
Experience the Request Flow in Action
Experience the Request Flow in Action
Watch how users can place a dataset request, preview it on the map, and access the API - all in just a few clicks.
Watch how users can place a dataset request, preview it on the map, and access the API - all in just a few clicks.
See Compare Mode Bring Data to Life
See Compare Mode Bring Data to Life
Watch how users can overlay and contrast two datasets using side-by-side, slider, or opacity views - making changes easy to spot.
Watch how users can overlay and contrast two datasets using side-by-side, slider, or opacity views - making changes easy to spot.
Problem Statement
A broken data access experience was delaying sales, frustrating users, and limiting the adoption of company’s most valuable datasets.
A broken data access experience was delaying sales, frustrating users, and limiting the adoption of company’s most valuable datasets.
Solution
Faster Access – Self-serve dashboard for quick dataset discovery & API access.
Clear Insights – Interactive maps with legends & powerful Compare mode.
Easy Integration – One-click API copy & secure key handling.
Built to Scale – Design patterns that became SatSure’s first design system.
Results
50%
50%
reduction in time spent on searching for API in email.
3x
increase in internal team productivity by automating data access.
30%
boost in sales conversions due to faster, data-driven client pitches.
context
Getting to know Sparta
SatSure is geospatial company that uses satellite data to solve real-world problems.
Sparta is the core business unit of SatSure. It's the backend platform for the company's other products, built entirely on the cloud. It manages and delivers data to both internal and external users.
SatSure is geospatial company that uses satellite data to solve real-world problems.
Sparta is the core business unit of SatSure. It's the backend platform for the company's other products, built entirely on the cloud. It manages and delivers data to both internal and external users.
Imagine walking into a library full of books (each book being a dataset), but you're struggling to find what you need, fast.
That’s where Sparta was facing a challenge - users were lost in the system, unsure which dataset to pick, when, and how.
struggle
Amit, a sales manager, searches for rainfall data but finds 20 unlabeled datasets. No filters. No preview. Just chaos.
Ting! Slack messages fly.
"Try dataset_001_v2_final?" “Ask GIS team?” Time ticks. Frustration builds.
One hour gone. No dataset selected. No progress made. Amit’s pitch slips, again.
Instead of jumping straight into user interviews, I spent a day using the previous version of the tool myself. Experiencing the frustrations firsthand helped me relate more deeply to our users and allowed me to ask more targeted questions during the interviews. It felt like I was stepping into their shoes and experiencing their pain points directly.
Instead of jumping straight into user interviews, I spent a day using the previous version of the tool myself. Experiencing the frustrations firsthand helped me relate more deeply to our users and allowed me to ask more targeted questions during the interviews. It felt like I was stepping into their shoes and experiencing their pain points directly.
issues with older version
The earlier Sparta platform was outdated and difficult to use
Limited options to request or filter datasets
Only static data samples, no interactive exploration
Missing basic map features like date selection or legends
Poor data formatting and lack of readability
No login or way to track user behaviour
Missing or inconsistent documentation
The earlier Sparta platform was outdated and difficult to use
Limited options to request or filter datasets
Only static data samples, no interactive exploration
Missing basic map features like date selection or legends
Poor data formatting and lack of readability
No login or way to track user behaviour
Missing or inconsistent documentation
It lacked the structure, clarity, and usability needed for scalable adoption.
Older Version
Older Version
user interview
🎧 Listening to Users
At first glance, it seemed obvious what needed fixing. We already knew the older version had problems - confusing flows, no dataset previews, lots of manual steps. So the natural instinct was to jump straight into solutions.
But once we began talking to people : sales managers, PMs, geospatial analysts, engineers - things started surfacing that we hadn’t anticipated. We uncovered how data actually moved through the system, what broke in handoffs, and where real friction lived.
These weren’t just interviews. They turned into early ideation rooms : where half-baked thoughts sparked better ones, and problems began unraveling into design opportunities. And for me, fresh in the company, it became the fastest way to build both context and trust.
At first glance, it seemed obvious what needed fixing. We already knew the older version had problems - confusing flows, no dataset previews, lots of manual steps. So the natural instinct was to jump straight into solutions.
But once we began talking to people : sales managers, PMs, geospatial analysts, engineers - things started surfacing that we hadn’t anticipated. We uncovered how data actually moved through the system, what broke in handoffs, and where real friction lived.
These weren’t just interviews. They turned into early ideation rooms : where half-baked thoughts sparked better ones, and problems began unraveling into design opportunities. And for me, fresh in the company, it became the fastest way to build both context and trust.
External Users
Agriculture professionals using satellite insights to make informed, time-sensitive decisions.
Agriculture professionals using satellite insights to make informed, time-sensitive decisions.
“I’m not sure if the data I'm seeing even fits my region or timeline.”
“We need to preview data before building anything on top of it.”
“I’m not sure if the data I'm seeing even fits my region or timeline.”
“We need to preview data before building anything on top of it.”
Internal Users
Sales managers, product managers, and geospatial analysts who rely on smooth access to datasets.
Sales managers, product managers, and geospatial analysts who rely on smooth access to datasets.
“Finding the right API or dataset takes too many steps.”
“We often go back and forth on Slack just to clarify what the data even contains.”
“Finding the right API or dataset takes too many steps.”
“We often go back and forth on Slack just to clarify what the data even contains.”
Despite differences in roles, a common thread emerged:
Despite differences in roles, a common thread emerged:
Everyone needed faster, more intuitive access to datasets.
Everyone needed faster, more intuitive access to datasets.
problem breakdown
Addressing the core problems
Building on our earlier analogy, users felt lost and confused while searching for the right books, highlighting the need for a catalog.
To validate this problem, as we spoke to users and identified few more problems or issues caused because of this :
Building on our earlier analogy, users felt lost and confused while searching for the right books, highlighting the need for a catalog.
To validate this problem, as we spoke to users and identified few more problems or issues caused because of this :
Key issues identified
🔎 Poor Discoverability
🔎 Poor Discoverability
No structured way to explore or filter datasets
Hard to find data relevant to specific business needs
Sales teams couldn’t easily showcase datasets
No structured way to explore or filter datasets
Hard to find data relevant to specific business needs
Sales teams couldn’t easily showcase datasets
🗺️ Lack of Visualization
🗺️ Lack of Visualization
No map preview for datasets like NDVI or rainfall
Static samples offered little clarity
Couldn’t compare datasets across time or geography
No map preview for datasets like NDVI or rainfall
Static samples offered little clarity
Couldn’t compare datasets across time or geography
🤝 Manual Access
🤝 Manual Access
APIs shared via email chains
Too many people involved to get data
No central place to preview or validate requests
APIs shared via email chains
Too many people involved to get data
No central place to preview or validate requests
🧩 Difficult Client Integration
🧩 Difficult Client Integration
Clients relied on system integrators to use data
Adoption required custom manual setups
Clients relied on system integrators to use data
Adoption required custom manual setups
summing it up
A broken data access experience was delaying sales, frustrating users, and limiting the adoption of SatSure’s most valuable datasets.
A broken data access experience was delaying sales, frustrating users, and limiting the adoption of SatSure’s most valuable datasets.
Approach to the solution
From problem to possibilities
Once we had a clear picture of the problem and what users truly needed, our direction became obvious: the solution had to make API access simpler and data visualization intuitive.
We held several deep-dive sessions with the team - discussing not just what we wanted to build, but also why the earlier version fell short. A lot of those conversations revolved around broken flows, tech limitations, and things that simply didn’t scale. What we all aligned on was this: the new experience should feel effortless. A few clicks. The right dataset. That’s it.
We also talked through technical feasibility, phased rollouts, and constraints around timelines. While the team brainstormed backend and infrastructure needs, I spent time exploring how other platforms tackled similar problems.
I dug into API docs from platforms like PayU, Mailchimp, and UP42 to understand structure, clarity, and developer experience. Since one of our goals was to improve documentation, this helped me learn what good looks like.
I also researched geospatial platforms to understand how data gets visualized, zoomed into tools, file formats like .geojson, .kml, .tiff, and how they’re rendered on maps.
It was overwhelming at first - but incredibly rewarding. It gave me a clearer lens into what technical users actually care about.
With that foundation, we broke down the solution module by module - tackling real constraints, weighing trade-offs, and making decisions that balanced usability with scalability.
Let’s dive into how each of those modules came together.
Once we had a clear picture of the problem and what users truly needed, our direction became obvious: the solution had to make API access simpler and data visualization intuitive.
We held several deep-dive sessions with the team - discussing not just what we wanted to build, but also why the earlier version fell short. A lot of those conversations revolved around broken flows, tech limitations, and things that simply didn’t scale. What we all aligned on was this: the new experience should feel effortless. A few clicks. The right dataset. That’s it.
We also talked through technical feasibility, phased rollouts, and constraints around timelines. While the team brainstormed backend and infrastructure needs, I spent time exploring how other platforms tackled similar problems.
I dug into API docs from platforms like PayU, Mailchimp, and UP42 to understand structure, clarity, and developer experience. Since one of our goals was to improve documentation, this helped me learn what good looks like.
I also researched geospatial platforms to understand how data gets visualized, zoomed into tools, file formats like .geojson, .kml, .tiff, and how they’re rendered on maps.
It was overwhelming at first - but incredibly rewarding. It gave me a clearer lens into what technical users actually care about.
With that foundation, we broke down the solution module by module - tackling real constraints, weighing trade-offs, and making decisions that balanced usability with scalability.
Let’s dive into how each of those modules came together.
User Flow
Creating a user flow helped me break down the process into clear steps, making it easier to spot and fix potential issues early. This simplified the experience, allowing me to jump into high-fidelity designs with confidence and avoid time-consuming revisions later.
Creating a user flow helped me break down the process into clear steps, making it easier to spot and fix potential issues early. This simplified the experience, allowing me to jump into high-fidelity designs with confidence and avoid time-consuming revisions later.
#module 1
Request Flow - Taking Input from the User
The Request Flow is the entry point of the dashboard - where users specify what data they want, for which region, and during which time period.
The Request Flow is the entry point of the dashboard - where users specify what data they want, for which region, and during which time period.
#module 2
Request Repository - Centralized list of all queries.
After a user runs a request, the system logs it in the Request Repository, where all current and past requests are stored and tracked.
After a user runs a request, the system logs it in the Request Repository, where all current and past requests are stored and tracked.
Known Gaps & Reflections
While recent requests were available for comparison from the dashboard, older requests (visible only in the table view) were not eligible for comparison due to technical and time constraints.
This was flagged for future improvement — enabling comparison across full request history.
Known Gaps & Reflections
While recent requests were available for comparison from the dashboard, older requests (visible only in the table view) were not eligible for comparison due to technical and time constraints.
This was flagged for future improvement — enabling comparison across full request history.
#module 3
API Panel - The Heart of Data Access
The API Panel is central to the dashboard’s workflow, providing direct access to raw datasets for integration with internal systems or external tools.
The API Panel is central to the dashboard’s workflow, providing direct access to raw datasets for integration with internal systems or external tools.
What’s Happening Behind the Scenes?
Our platform sends a GET request to the SatSure server → retrieves metadata and dataset links → which users can copy and plug into their internal pipelines or tools.
Our platform sends a GET request to the SatSure server → retrieves metadata and dataset links → which users can copy and plug into their internal pipelines or tools.
#module 4
Map Visualisation & Compare Mode
The Map Visualisation was the core of the dashboard experience - where users viewed their requested data as a raster overlay on a geographic base map. This module wasn’t just about rendering layers; it was about making spatial data accessible, interactive, and comparable.
The Map Visualisation was the core of the dashboard experience - where users viewed their requested data as a raster overlay on a geographic base map. This module wasn’t just about rendering layers; it was about making spatial data accessible, interactive, and comparable.
Default View Map
Default View Map
Compare Mode
This was one of the biggest design breakthroughs in the project. I explored three visual comparison techniques and implemented all three for different use cases.
This was one of the biggest design breakthroughs in the project. I explored three visual comparison techniques and implemented all three for different use cases.
#1 Side-by-Side Map
Each pane renders a separate dataset.
Used for time-lapse analysis across seasons/months.
#1 Side-by-Side Map
Each pane renders a separate dataset.
Used for time-lapse analysis across seasons/months.
#2 Slider Comparison (Swipe)
A draggable divider reveals the second layer as you move across.
Ideal for pixel-level change detection.
#2 Slider Comparison (Swipe)
A draggable divider reveals the second layer as you move across.
Ideal for pixel-level change detection.
#3 Overlay with Opacity Control
Both layers stacked; user can toggle opacity.
Helpful for spotting overlaps or subtle shifts.
#3 Overlay with Opacity Control
Both layers stacked; user can toggle opacity.
Helpful for spotting overlaps or subtle shifts.
Before vs After
Before vs After
Retrospective
This project was a defining moment in my design journey - one that reinforced a fundamental truth: no matter how intricate the backend, the user interface must remain simple and intuitive.
This project was a defining moment in my design journey - one that reinforced a fundamental truth: no matter how intricate the backend, the user interface must remain simple and intuitive.
Fresh to the domain
Fresh to the domain
From transforming satellite data into meaningful experiences to shaping intuitive workflows, this experience has deepened my perspective as a designer.
From transforming satellite data into meaningful experiences to shaping intuitive workflows, this experience has deepened my perspective as a designer.
Designing with Constraints
Designing with Constraints
I learned the value of aligning design with technical constraints. Collaborating across teams and working closely with developers helped bridge vision and execution.
Compare Mode: A Small Feature with Big Impact
Compare Mode: A Small Feature with Big Impact
The Compare feature allowed users to overlay and visually compare datasets across time or types - turning raw data into real insight.
What started as a one-off feature evolved into a scalable design pattern, reused across other SatSure dashboards like insurance analytics and crop monitoring.
The Compare feature allowed users to overlay and visually compare datasets across time or types - turning raw data into real insight.
What started as a one-off feature evolved into a scalable design pattern, reused across other SatSure dashboards like insurance analytics and crop monitoring.
What This Project Sparked: A Design System Foundation
While building Sparta, one issue kept surfacing—there was no shared design language. Every button, spacing token, and dropdown had to be built from scratch.
So once the platform shipped, I took the lead in building SatSure’s first internal design system.
The result?
⏱️ 50% faster design output
✅ More consistent handoffs
🧩 A design foundation now used across every SatSure product
For this contribution, our team was recognized and I was awarded the Product Champion of the Quarter.
While building Sparta, one issue kept surfacing—there was no shared design language. Every button, spacing token, and dropdown had to be built from scratch.
So once the platform shipped, I took the lead in building SatSure’s first internal design system.
The result?
⏱️ 50% faster design output
✅ More consistent handoffs
🧩 A design foundation now used across every SatSure product
For this contribution, our team was recognized and I was awarded the Product Champion of the Quarter.