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Buddy Up

LifeStyle

Involvement

Product Strategy

Full-Stack Development

AI/ML Engineering

Cloud Architecture

DevOps

BuddyUp is an intelligent housemate matching platform that revolutionises the roommate search experience through ML-powered compatibility algorithms, location-based isochrone analysis for commute optimisation, and inclusive identity verification. The platform combines sophisticated recommendation technology with a safety-first approach to create an LGBTQ+ friendly community for finding compatible living arrangements.

Problems

Inefficient Search Process:

Traditional housemate hunting involves countless hours browsing listings and messaging incompatible people, leading to frustration and wasted time with no guarantee of finding the right match

Safety & Compatibility Concerns:

Users face risks from unverified profiles and catfishing, whilst LGBTQ+ individuals often encounter unsafe verification processes that don't accommodate their identity

Solutions

Smart Compatibility Matching:

Built a sophisticated ML recommendation engine using collaborative filtering and hybrid algorithms that analyse lifestyle preferences, schedules, cleanliness habits, and personality traits to surface highly compatible housemate matches.

Location Intelligence System:

Implemented isochrone-based mapping that calculates commute times to users' workplaces/universities and automatically identifies optimal neighbourhoods where both parties can live together within their desired travel times.

Mutual Interest & Safety Framework:

Created a double opt-in messaging system preventing inbox spam by ensuring users can only communicate when both parties express interest, combined with robust ID verification to eliminate catfishing.

Real-Time Communication & Property Sharing:

Developed instant messaging functionality with real-time chat features allowing matched users to communicate seamlessly, share property listings, and coordinate viewing schedules—all within a single platform.

What we did?

Conducted user research with 50+ renters to understand pain points in the housemate search journey.
Built interactive prototypes with location-based matching simulations to validate the concept.
Implemented cross-platform mobile development with Flutter for iOS and Android deployment.
Integrated ML models with real-time recommendation updates and A/B testing framework.
Deployed scalable microservices architecture with comprehensive API testing and monitoring.
Launched production-ready app to both app stores within 16 weeks from discovery to release.

Key Results & Impact

75 %

Time Savings

Users find compatible housemates in an average of 8 days vs. 4-6 weeks with traditional platforms like SpareRoom or Craigslist.

75 %

Time Savings

Users find compatible housemates in an average of 8 days vs. 4-6 weeks with traditional platforms like SpareRoom or Craigslist.

75 %

Time Savings

Users find compatible housemates in an average of 8 days vs. 4-6 weeks with traditional platforms like SpareRoom or Craigslist.

92 %

Match Satisfaction Rate

Post-move surveys show 92% of users who moved in together remain satisfied with their housemate after 6 months, compared to 60% industry average

92 %

Match Satisfaction Rate

Post-move surveys show 92% of users who moved in together remain satisfied with their housemate after 6 months, compared to 60% industry average

92 %

Match Satisfaction Rate

Post-move surveys show 92% of users who moved in together remain satisfied with their housemate after 6 months, compared to 60% industry average

This project demonstrates our capability in building complex, ML-driven mobile applications with sophisticated matching algorithms, real-time features, and inclusive design principles—delivering measurable impact on user experience, safety, and community building.

Tech Stack

Flutter

Node.js / TS

Python / FastAPI

PostgreSQL

MongoDB

Redis

AWS

TensorFlow

Kubernetes

PostGIS

Client Testimonial

"Abdeali and the Siya team have been a great to work with. We came with an early concept and a comprehensive list of requirements. The team were able to build multiple products quickly whilst maintaining high quality in a short timeframe. They also try to be forward thinking with the goal of keeping the project timeline on track. Based on my experience, I'd highly recommend them to any early stage startup."

Nikian

Founder

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Buddy Up

LifeStyle

Problems

Inefficient Search Process:

Safety & Compatibility Concerns:

Solutions

Smart Compatibility Matching:

Location Intelligence System:

Mutual Interest & Safety Framework:

Real-Time Communication & Property Sharing:

What we did?

Key Results & Impact

75

%

75

%

75

%

92

%

92

%

92

%

This project demonstrates our capability in building complex, ML-driven mobile applications with sophisticated matching algorithms, real-time features, and inclusive design principles—delivering measurable impact on user experience, safety, and community building.

This project demonstrates our capability in building complex, ML-driven mobile applications with sophisticated matching algorithms, real-time features, and inclusive design principles—delivering measurable impact on user experience, safety, and community building.

Tech Stack

Client Testimonial

Client Testimonial

Nikian

But struggling on where to start?

Explore More

Alvie

Martyn

Studeo

Antonin

SuperRise

Bettina

Connect. Create.

Cultivate Success.