Turn your data into a distinct visual identity that remains consistent across outputs. Generate unique aesthetics and IP shaped by your data’s structure and behaviour. Apply a recognisable signature to every image, surface, or system.
Digital watermarking
Embed persistent digital signatures into your visuals, audio, and environments. Protect authorship and track origin across formats and transformations. Maintain verification without altering the visible output.
Immersive Storytelling
Transform your data into spatial, sensory environments. Generate installations using light, sound, and responsive systems. Experience complex data as dynamic, evolving spaces.
Transform your data into spatial, sensory environments. Generate installations using light, sound, and responsive systems. Experience complex data as dynamic, evolving spaces.
InterWorld is an AI-driven platform for data-driven aesthetics, developed as a response to energy-intensive systems and synthetic media such as deepfakes.
It produces outputs shaped by specific datasets, avoiding generic, mass-generated visuals, with traceable and verifiable origin.
Resource-aware, accountable, and built for distinct aesthetic outcomes.
We work with small datasets and energy-conscious systems. Our installations are designed to operate with minimal computational overhead, offering an alternative to resource-intensive generative pipelines and the increasingly uniform aesthetics that accompany them
We develop unique visual and sonic languages that retain character across media, resisting homogenising aesthetics of popular AI generators.
Our approach treats data as an active medium. We construct narratives through data and with data, allowing it to be continuously reworked, reintroduced, and reinterpreted across the system rather than fixed as a finite resource.
Outputs of the fine-tuned AI environment initially clustered based on similarity
(t-SNE grouping).
Outputs of the experimental AI environment Polymorph first dispersed through the standard t-SNE similarity-based grouping, then re-clustered through flocking behaviour, resisting the narratives of data finitude.