CoLive
Turning Shared Spaces into Shared Comfort.
Created on 7th February 2026
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CoLive
Turning Shared Spaces into Shared Comfort.
The problem CoLive solves
Finding a place to live is hard but finding the right people to live with is even harder—and that’s the real problem most platforms ignore. Students and young professionals often end up sharing spaces with strangers without knowing anything about their habits, schedules, cleanliness, budgets, or personalities. This leads to daily friction, unsafe situations, mental stress, and frequent relocation. CoLive-Match addresses this gap by focusing on people compatibility before property. Instead of just listing rooms, it helps individuals find roommates whose lifestyle, routines, and expectations align with theirs. It reduces conflicts, saves time lost in trial-and-error housing, and creates safer, more stable co-living environments—something current rental and PG platforms don’t actively solve.
In short, it shifts the focus from “finding a room fast” to “finding the right people to live with,” making co-living more stable, transparent, and easier to manage.
Challenges we ran into
One of the biggest challenges while building Colive-Match was designing a system that actually matches people based on lifestyle compatibility, not just basic filters like budget or location. Early on, the matching logic felt too generic — it was giving similar results to any rental listing platform, which defeated the core purpose of the product.
We also ran into issues while structuring user inputs. People describe habits differently (for example, “late sleeper,” “night owl,” “works night shifts”), and converting that into something measurable for matching wasn’t straightforward. This led to inconsistent results during testing.
To solve this, we reworked the onboarding questions to be more behavior-focused and standardized the options instead of relying on open text. On the technical side, we simplified the compatibility logic first, tested it with small datasets, and then gradually layered more conditions. Iterating like this helped us move from a vague idea of “matching roommates” to something that actually reflects how people live day-to-day.
Another hurdle was making the interface feel trustworthy and not like a typical listing site. We kept refining the layout and flow until it felt more like a guided decision process rather than just browsing rooms.
Tracks Applied (1)
Open Innovation
Technologies used