LIVE PROJECT
Skyline Robotics
B2B SaaS Platform for Robotic Window Cleaning Operations
Skyline Robotics builds autonomous robots for window-cleaning skyscrapers.
While the hardware was groundbreaking, the company lacked a dedicated data product for its clients.
As the sole product designer, I defined and built the SaaS dashboard from the ground up, while also redesigning the robot’s technical interface. My work focused on transforming complex data into functional tools to support real-time monitoring and spatial asset management for enterprise clients.
PROJECT OVERVIEW
Role
Solo Product Designer
Timeline
Jan 2024 - Present
Team
1 Designer, 4 Engineers
Platforms
Web Dashboard, Operator Interface
THE CHALLENGE
Problem & Solution
The Gap
Data was siloed in logs and internal tools, accessible only to engineers. Fleet managers and building owners were "blind" to real-time fleet status, creating dependency bottlenecks.
PAIN POINTS
Complete dependency on engineering team for status updates
Slow response times to operational issues
Lack of client confidence due to limited transparency
No historical data for performance analysis
The Solution
visibility comes before analysis
A unified real-time visibility platform where Fleet Managers have a single source of truth. The core principle: "Users need to know what's happening NOW."
KEY FEATURES
Real-time fleet status across all global locations
Drill-down hierarchy: Fleet → Area → Building → Window
Integrated environmental data (weather, wind) in one view
Anomaly detection and automated alerts
CONSTRAINTS
01
Technical complexity of real-time robot data
02
Legacy API limitations
03
Accessibility for non-technical users
04
Multi-stakeholder approval process
05
Limited development resources
SUCCESS CRITERIA
Rapid learning curve
Increase client engagement
Decrease support tickets
Seamless fleet expansion and multi-asset management
Standardized Asset Onboarding
KEY PERSONAS
User Needs
Mike
Cleaning company owner / Client
Late-40s • Business-focused • ROI-driven
PRIMARY GOAL
Understand bottom-line business value, resource savings, and operational KPIs to justify the investment in autonomous systems.
NEEDS
High-level KPIs and cost savings metrics
Historical performance data and trends
Resource consumption comparisons (water, time)
Simple, executive-level dashboard view
QUOTE
"Show me the ROI. How much time and money are we saving compared to traditional methods?"
David
Operations Manager
Mid-30s • Tech-savvy • Detail-oriented
PRIMARY GOAL
Monitor real-time robot performance with granular, window-by-window progress tracking to ensure client SLA compliance.
NEEDS
Instant visibility into robot status and location
Detailed progress metrics per building
Immediate alerts for operational issues
Weather/environmental context in one view
QUOTE
"I need to see what's happening RIGHT NOW, not dig through logs to find out if we're on schedule."
INFORMATION ARCHITECTURE
Defining System Flows: Bridging User Needs through Information Architecture
To bridge the gap between Mike's high-level business needs and David's granular operational requirements, I designed a 4-level drill-down architecture. This flow ensures that data is never overwhelming; it moves logically from a Global Fleet Overview (Level 1) down to a specific Window-Level status (Level 4). This structure transformed fragmented engineering logs into a coherent, actionable tool for all stakeholders.
Global Fleet Overview
Mike's KPI View • High-level business metrics
Entry Point
NYC (ex.) Map & Building List
Filter by region • Spatial context
Specific Area
Window-by-Window Progress
David's operational view • Real-time data
Building Detail
Analytics
Operational KPIs • Resource Trends
Management
PERSONA: BUSINESS STAKEHOLDER (MIKE)
LEVEL 1 • ENTRY POINT
Global Fleet Overview
Mike's KPI View • High-level business metrics
Filter by Region
LEVEL 2 • REGIONAL
NYC Regional Map & Building List
3D map view • Status-coded building list
Select Specific Building
PERSONA: OPS MANAGER (DAVID)
LEVEL 3 • GRANULAR DETAIL
Building Deep-Dive
David's operational command center
• Real-time progress grid (window-by-window status)
• Weather/Wind monitoring (integrated environmental data)
• Facade switching (North, South, East, West views)
Drill-down
Technical
Anomaly?
YES
Analyze Anomaly
NO
Continue Monitoring
LEVEL 4 • OPERATIONAL ACTION
Analytics & Fleet
Back-office controls for technical teams
• Operational KPIs • Resource Trends • Reports
Configure Fleet
FINAL OUTPUT
Export Data / Download Completion Report
Stakeholder reporting • Client deliverables
DESIGN IMPACT
Bridging the Gap
This drill-down architecture
transformed fragmented
engineering logs into a
coherent, actionable tool
SCREEN 1 OF 6
Global Fleet Overview
High-level dashboard showing total robots across cities with resource-saving KPIs prominently displayed at the top. Designed for executive-level visibility.
Performance Trends
Historical data visualization showing efficiency improvements over time.
City Distribution
Visual breakdown of fleet distribution across global locations with status indicators.
KPI Cards
Total robots, active jobs, and resource savings highlighted for immediate business value assessment.
SCREEN 2 OF 6
Regional Drill-Down (NYC)
3D map provides spatial context while building list shows status-based color coding (Online/Issue). Integrated weather/wind widget eliminates app-switching for operators.
3D Map Navigation: Visual Asset Sync
THE CHALLENGE
While a 3D map was a core requirement, navigating a dense urban environment with dozens of identical-looking buildings proved difficult.. This led to cognitive load and user disorientation during high-pressure operational tasks.
THE SOLUTION
I designed a visual "bridge" between the technical data and the map.. Selecting a building from the list instantly highlights its 3D model in Amber (#FFB000), allowing for immediate spatial recognition and zero search time.
TECH NOTE
Reduces time-to-action by 40% in critical warning scenarios.
FEATURE SPOTLIGHT
Weather Widget
Integrated environmental data showing temperature, wind speed, and operational safety thresholds.
Status Indicators
Color-coded building list with Online (green), Warning (yellow), and Issue (red) states.
SCREEN 3 OF 6
Building Deep-Dive
Window-grid interface showing real-time progress (e.g., 152/200 windows cleaned). Includes facade switching and historic cycle data for detailed operational insight.
Historic Cycles
Timeline view showing past cleaning cycles and completion rates for performance tracking.
Facade Switching
Toggle between North, South, East, and West facades to monitor multi-sided operations.
Window Grid
Visual grid representation of building facade with real-time cleaning status per window.
Granular Analytics & Anomaly Detection
This screen demonstrates the transition from global fleet data to a single-building drill-down view. Real-time KPIs, anomaly detection, and progress tracking converge to give managers instant situational awareness.
SCREEN 4 OF 6
Granular Fleet Management
Enabling a 'Macro to Micro' workflow where managers can transition from a high-level fleet overview to specific building analysis (e.g., Bank of America Tower).
Deep-dive: Real-time localized data filtering
Business Value KPIs
Top-level cards display Estimated Annual Savings ($342,000) and Operational Hours Saved (2,500 h) with year-over-year growth indicators.
vs. Traditional Cleaning: 8% improvement
Progress Tracking
'Completed Drop' widget shows 152/200 (76%) progress with daily average metrics for immediate situational awareness.
Total vs. Daily Avg visualization
Trend analysis over time
Performance Benchmarking
Comparative visualization of current resource consumption against historical averages to ensure operational consistency.
Identifying resource usage spikes
Real-time threshold monitoring
Operational Analytics
Data cards for water consumption with anomaly detection and completed drop statistics. Designed for sustainability reporting and operational efficiency analysis.
SCREEN 5 OF 6
Performance Scores
Automated scoring system comparing actual vs. expected performance per building.
Completed Drops
Historical data showing total operations completed with efficiency metrics.
Water Consumption
Real-time monitoring with anomaly detection alerts for abnormal usage patterns.
Setting the Tone: Facade Analytics
The entry point to the platform emphasizes data accessibility. The branding and illustration highlight our core mission: providing clarity and visibility beyond the traditional four walls of building management.
SCREEN 6 OF 6
Minimalist UX
Streamlined authentication flow removes friction while maintaining enterprise security standards.
Visual Metaphor
AI-generated illustration communicates the platform's mission: data visibility beyond traditional boundaries.
Brand Identity
Clean Skyline Robotics branding establishes trust and professionalism from first interaction.
RESULTS
Impact & Outcomes
0 to 100%
Transitioned from raw engineering logs to a unified, real-time operational dashboard
DATA VISIBILITY
- 50%
Reduced engineering dependency, resulting in a 50% decrease in technical support tickets.
SUPPORT TICKET
100%
Fleet managers can now monitor all global assets without technical engineering knowledge
FLEET ACCESSIBILITY
Key Learnings
Dual Persona Design
Serving both operational detail (David) and executive overview (Mike) required flexible
drill-down architecture.
System Standardization
A modular design system allowed the platform to scale its data architecture even while the product was in rapid MVP stages.
Visibility First
Prioritizing "What is happening now" over historical analysis was the key to user adoption.
Operational Efficiency
Integrating weather and wind data directly into the map reduced decision-making
time significantly.
METHODOLOGY
Design Process
01
Discovery
Stakeholder interviews with ops managers, building owners, and engineering team. Identified core pain point: lack of real-time visibility.
User interviews
Competitive analysis
Technical constraints mapping
02
Information Architecture
Designed drill-down hierarchy (Fleet → City → Building → Window) based on user mental models and operational workflows.
IA diagrams
Content taxonomy
Navigation structure
03
User Flows & Wireframing
Mapped critical paths for both personas: quick status check vs. deep analytical dive. Prioritized speed and clarity.
User flow diagrams
Lo-fi wireframes
Task analysis
04
Visual Design & Prototyping
Built high-fidelity designs with technical precision. Emphasized data density without overwhelming users.
Hi-fi mockups
Interactive prototypes
Design system components
05
Testing & Iteration ↺
Enabled internal team prototype testing and gathered user feedback
via survey.
Prototype testing sessions
CEO-mediated survey
Design iteration cycles
06
Implementation Support
Worked closely with R&D team during development. Created detailed specs and maintained design QA throughout build.
Developer handoff docs
Component specs
QA reviews
Let’s Talk
I’m currently seeking my next full-time challenge where I can solve complex problems and grow alongside a talented team.
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