Karavela AI is developing a large-scale artificial intelligence model of the human brain to support diagnostics and brain-computer interface applications. The company is building what it describes as a foundation model for brain activity, trained on large volumes of task-based fMRI data to learn general representations of neural function. By modelling patterns of activation and connectivity across different tasks and individuals, the platform is designed to support biomarker discovery, disease detection, and neural signal decoding. Karavela positions its work at the intersection of neuroimaging, machine learning, and computational neuroscience.

The platform is built on extensive fMRI datasets collected across a range of cognitive tasks, which are used to train deep learning models on large-scale patterns of brain activity. This approach is intended to capture generalizable features of functional brain organization that can be adapted for downstream use cases. In diagnostic settings, the model could help identify deviations from expected neural patterns that may signal disease. In BCI contexts, it could serve as a pretrained layer for decoding brain signals by supplying a richer prior model of brain dynamics.

Karavela’s technology is aimed at both clinical and research applications. In diagnostics, it could support the development of MRI-based biomarkers for neurological and psychiatric conditions. In BCI, it may improve decoding performance in neuroimaging-driven systems. More broadly, the platform reflects a growing effort to apply foundation-model logic to brain data, using large-scale AI systems to extract structure from complex neural signals.