SomePlace

This project started during the design a thon from something deeply personal to us as Persian immigrants living far from home, where many of the places that shaped our memories are not only distant but sometimes at risk of being lost due to war. We realized that what we were feeling was not just nostalgia, but a kind of quiet confusion. We would try to find places in a new city that reminded us of home, but everything felt random. We did not know what to search for, and even when something looked right, it often did not feel right. That sense of chaos became the starting point of our idea.

Through quick user research, conversations, and empathy mapping, we saw that this was not just our experience. Many people expressed similar feelings of disconnection, saying things like nowhere fits me or something feels off compared to what I remember. This is where the theme of the design a thon, Chaos into Clarity, became very real for us. The chaos was not just information overload, but emotional noise. People had fragmented memories, unclear needs, and no clear way to express what they were looking for.

To address this, we directly drew inspiration from how people use Notability. In our process, we used a Notability like approach to simulate real user behavior by capturing incomplete inputs such as short phrases, quick notes, photos, and keywords like warm lighting, quiet, or old café feeling. This helped us design an interface that allows users to express themselves in fragments instead of forcing them into rigid filters or predefined categories.

We then applied ideas inspired by Google Gemini to interpret these fragmented inputs. We treated Gemini as a model for how different types of input such as text, images, and vague descriptions can be understood together. In our design, we translated user inputs into a set of atmospheric features like lighting, sound level, cultural cues, and social density. These features were then used to generate place suggestions based on emotional similarity rather than traditional labels.

For example, instead of searching for a Persian café, a user can describe a feeling like a quiet place with soft music and warm light. The system interprets this into meaningful attributes and suggests places that recreate that atmosphere, even if they are not culturally identical. This is how we move from chaos to clarity, by interpreting ambiguity instead of forcing precision.

Our design process was highly iterative. We sketched, simplified, and tested continuously, often using Notability to check whether the system could handle messy and incomplete expression. One of the biggest challenges was designing for something as abstract as emotions while keeping the experience simple and intuitive. Another challenge was avoiding unnecessary complexity. We learned that clarity comes from reducing friction and shaping complexity into something calm and understandable.

In the end, this project became a direct reflection of the design a thon’s core idea. By combining Notability inspired input with Gemini inspired interpretation, we created a system that turns emotional chaos into meaningful experiences. It is not about perfect recommendations, but about helping people move from confusion to a small moment of recognition, where they walk into a place and feel a sense of familiarity.