TerraFlow
AI‑Powered CRM for Real Estate
Duration
8 months
Team Size
6 Members
My Role
Full Stack Engineer
Design Process
How We Built It
Field Research
Shadow sessions with 15 real estate agents to document daily workflows and tool switching pain.
Data Architecture
Designing the ML pipeline for lead scoring and the MLS data ingestion system.
Mobile-First Design
Component system built for touch-first interactions with high contrast for outdoor use.
Pilot & Iterate
Deployed to 3 real estate agencies. Iterated based on 8 weeks of production feedback.
Field Research
3 weeksShadow sessions with 15 real estate agents to document daily workflows and tool switching pain.
Data Architecture
5 weeksDesigning the ML pipeline for lead scoring and the MLS data ingestion system.
Mobile-First Design
4 weeksComponent system built for touch-first interactions with high contrast for outdoor use.
Pilot & Iterate
6 weeksDeployed to 3 real estate agencies. Iterated based on 8 weeks of production feedback.
User Research
What We Discovered
Agents miss follow-up windows on qualified leads due to context switching between tools.
Value of property transactions managed through the platform in the first year.
Reduction in administrative overhead through AI-powered workflow automation.
Live Prototypes
Alive by Design
Interactive high-fidelity prototypes — not screenshots. Click, explore, and experience the product as it was intended.
Alive Prototypes
High-Fidelity Interactive Experience
Lead Velocity
Conversion
Avg Deal
Market Insight
Demand for 3-bedroom lofts in LA is up 15%. Prioritizing matched leads.
Predictive Leads
AI-ranked by closing probability
Jonathan Wright
2m ago
Sarah Miller
15m ago
Robert Chen
1h ago
New Property Scan
Initialize AI matching engine for custom asset search
Top Match
For Sarah Miller
$1.45M
Los Angeles, CA
AI Recommendation
Market volatility signals high appreciation. Predicted 12% growth over 18 months.
Neural Property Matcher
Processing leads through 147 predictive dimensions
Network Topology
> CLASSIFYING PROPERTY ASSET_ID_4521 ...
> MATCHING SCORE: 0.9842 ...
> CONFIDENCE INTERVAL: 97.4% ...
Input Vectors
Model Status
HEALTHY
Active training on 1.2M recent transactions
Overview
Project Overview
TerraFlow revolutionizes real estate management by automating lead qualification, property matching, and client follow-ups. It leverages predictive analytics to identify high-value prospects.
Design Thinking
The Journey
User Flow & Architecture
Agent logs in -> Predictive dashboard shows 'Hot' leads -> One-click property match sent to client -> Automated follow-up triggered via SMS.
The Challenge Journey
Focused on the 'Agent on the Move'. We prioritized mobile usability and real-time notifications to ensure leads are handled within seconds of appearing.
Design Rationale
The UI uses high-contrast typography and clear CTA buttons (Lead Qualification) to minimize friction in fast-paced environments.
Visual Identity
Color System
Every color is intentional. The palette communicates trust, energy, and precision — chosen through user testing to evoke the right emotional response.
Emerald
primary
#10b981Green Deep
secondary
#059669Mint
accent
#6ee7b7Dark Slate
background
#020617Typography System
Type in Motion
Display / Heading
abcdefghijklmnopqrstuvwxyz
Body
The quick brown fox jumps over the lazy dog. Efficient design communicates meaning with clarity.
InterAccent / Code
const result = await ai.generate();
JetBrains MonoProblem Solving
Challenges & Solutions
Key Challenges
- Integrating with legacy MLS systems and normalizing disparate data formats.
- Creating accurate predictive models for property value trends.
- Building a mobile-first experience for agents on the go.
Strategic Solutions
- Built a robust data ingestion pipeline using Python and Airflow.
- Developed a hybrid mobile app using React Native for cross-platform support.
- Implemented automated SMS and email workflows using Twilio and SendGrid.
Results
Measurable Impact
Numbers that prove the design decisions made a real difference in the real world.
Increased agent lead conversion rates by 25%.
Reduced administrative overhead by 40% through automation.
Processed over $500M in property transactions in the first year.
Project Metadata
- IndustryEnterprise CRM
- Timeline8 months
- Team6 members
- RoleFull Stack Engineer