A photo of a rooftop party with a song playing underneath tells you something. It tells you what the person who posted it was feeling. It does not tell you whether the music was actually loud, whether the crowd was buzzing, or what it sounded like to be standing there. That gap is what Humm is built around.
Abhijai noticed the pattern watching Instagram stories from cafes, libraries, gardens, and parties. The music made the images feel alive - a silent image of a dance floor does not carry the same energy as the same image with a beat underneath. But the song was always the poster's choice, layered on top after the fact. The acoustic reality of the place - the actual ambience - was absent.
The missing metric, as Abhijai frames it, is the sound of being there. Not a track chosen in the editing screen, but a live reading of the environment: the volume, the energy, the acoustic character of the moment as it happens.
A Score You Capture on Location
Humm lets users generate a vibe score while they are physically at a place. The score is recorded live - in the moment, at the venue - rather than assigned or selected after the fact. It can then be shared alongside photos and videos as a piece of contextual data about what the experience actually felt like acoustically.
The distinction matters for how people read shared content. A beach photo with a score captured on the beach carries different information than the same photo with a song picked from a playlist. One tells you what someone chose to associate with the moment. The other tells you something about the moment itself.
Abhijai sees the vibe score becoming a standardised metric for sharing experiences - a new layer of information that sits alongside the image and the caption and says something that neither of those can say on their own.
Humm is available on the Google Play.
