Simplifying Rental Workflows Through AI
Reducing operational complexity for landlords through AI-powered workflows.
Role
Product Designer
Year
2024
Type
GenAI, Automation, SaaS
Project Summary
Independent landlords manage rentals across disconnected tools leading to missed messages, slow responses, and operational chaos.
A GenAI-powered SaaS workspace that centralizes messaging, leasing, maintenance, and marketing in one place.
Reduced operational overhead for small landlords, with AI automating the most repetitive and time-consuming tasks.
Product Designer end-to-end UX, user research, and interaction design across a 4-month sprint.
Overview
Cortado is a GenAI-powered rental management SaaS designed to simplify the day-to-day operations of independent landlords and small property managers. The goal was to reduce fragmentation across tools and automate repetitive work by bringing messaging, leasing, pricing, and maintenance into one AI-assisted workspace.
This project was completed during a fast-paced design sprint, focused on identifying real user pain points and validating a clear product direction in a short timeframe.
My Role
Research Synthesis
Reviewing and synthesizing insights generated from the design sprint
Experience & UX
Translating research outcomes into product concepts and UX decisions
UI Design
Designing key UI screens and interaction patterns
Design System
Supporting the team with visual clarity and system-level consistency
Understanding the Users
Reviewing the outcomes of the design sprint revealed a clear pattern in how rental operators work today:
Work is fragmented across too many tools
Listings, guest communication, pricing, and operations live in separate platforms, forcing constant context switching.
Guest communication dominates daily work
Responding to repetitive guest messages takes up several hours a day and frequently interrupts higher-value tasks.
Automation must remain transparent
Operators are open to AI assistance, but only when they can understand, review, and stay in control of system actions.
These takeaways shaped both the product scope and how AI would be positioned within the experience.
Design Focus
Based on the synthesized insights, guest messaging emerged as the highest-impact area for improvement.
My design work focused on:
Reducing cognitive load in message-heavy workflows
Making AI assistance visible without feeling intrusive
Supporting fast decisions while preserving user control
Structuring complex information into calm, scannable layouts
Solution
An AI-Assisted Inbox
The core experience centers around an AI-assisted inbox designed to help operators respond to guests faster and more confidently.
Rather than fully automating communication, the inbox:
Suggests draft replies that users can review and edit
Pulls context from reservations, policies, and property data
Learns from user feedback to improve future suggestions
This approach balances efficiency with trust, keeping users in the loop at all times.
Reflection
Designing operational workflows meant balancing efficiency with trust. While AI helped streamline repetitive tasks, the experience still needed to feel transparent and controllable for property managers handling day-to-day operations.
This project reinforced the importance of reducing complexity without oversimplifying workflows. Small interaction decisions had a meaningful impact on usability, clarity, and confidence across the platform.
Further Reading
Explore the full case study
A deeper breakdown of the project, process, and collaboration is available on Loka's website.
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