How We Built a Stay Management Platform for a US-Based Startup

Client Overview

Our client is a US-based startup focused on providing temporary emergency housing to individuals and families in crisis situations. They work closely with government agencies, healthcare providers, and nonprofits to connect people in urgent need with nearby hotels that have available rooms.

Their goals were clear:

Provide emergency shelter to individuals and families in crisis.
Ensure secure booking and data handling for sensitive cases.
Streamline coordination between agencies, case managers, and hotels.

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The Challenge

The client was managing reservations manually using spreadsheets and emails, which made it difficult to:

Respond quickly to urgent housing requests
Track room availability and booking status in real time
Coordinate with hotel partners and case managers
Ensure secure data handling for sensitive user information

They needed a centralized platform to automate bookings, streamline communication, and provide visibility across all stakeholders—without compromising security or speed.

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Our Solution: Stay Management

We designed and developed a custom stay management platform tailored for emergency housing needs.

View real-time room availability across partner hotels.
Manage check-ins, checkouts, and special accommodation requests.
Track usage and generate reports for partner agencies

Built with speed, reliability, and privacy in mind, the platform supports both mobile and desktop access, making it easy for field workers to respond quickly in time-sensitive situations.

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Technology Stack Behind the AI Chatbot

Frontend

The platform's frontend was developed using Next.js and React, ensuring high performance and responsiveness across devices. We utilized Chakra UI for a modular and accessible component system, enabling rapid UI development with a clean, intuitive user experience. This setup allowed us to cater to both residents and administrators with ease.

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Backend

The backend architecture leveraged AWS Lambda for serverless compute, enabling the application to scale effortlessly during high-demand situations. We used DynamoDB for fast, low-latency data access and Amazon Cognito for secure user authentication and management. Additionally, AWS SES and SNS were integrated for real-time communication via automated email and SMS alerts, ensuring stakeholders remained informed without delay.

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Deployment

Deployment was managed through Vercel for the frontend, enabling instant global delivery and efficient rollbacks. The backend was hosted fully on AWS, ensuring scalability, reliability, and operational resilience. Vercel Insights and Google Analytics were used to monitor performance and user behavior, driving continuous improvements post-launch.

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How We Did It: Step-by-Step

Goal Alignment & Workflow Mapping: We kicked off with discovery workshops involving case managers, hotel partners, and internal operations teams.
Design & Prototyping: Using Figma, we created wireframes and a clickable prototype focused on speed and ease of use for field workers.
Agile Development: We implemented the core features in sprints: hotel directory, real-time booking, messaging, role-based access, and reporting tools.
Security & Compliance Setup: AWS Cognito was integrated for secure login and role management. Data stored in DynamoDB followed best practices for encryption and access control.
Deployment & Rollout: The frontend was deployed via Vercel for quick iterations. The backend was serverless, ensuring cost-efficiency and scalability during emergencies.

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Results After Implementation

Reduced booking time

Before

20+ Mins

After

Under 5 mins

Automated Communication

Before

After

90%

Coordination

Before

Nothing

After

Across 30+ partners

Real Time Visibility

Before

After

Yes

Fully Secure

Before

After

Yes

How We Built a Stay Management Platform for a US-Based Startup

Client Overview

The Challenge

Our Solution: Stay Management

Technology Stack Behind the AI Chatbot

Frontend

Backend

Deployment

How We Did It: Step-by-Step

Results After Implementation

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