Brain-inspired Models
Architectures shaped by cortical principles for robust and efficient learning.
Learn morePioneering the intersection of AI and Neuroscience
We build brain-inspired intelligence and decode complex neural patterns to advance science, medicine, and human potential.
From signals to understanding
WaxBrain fuses large-scale AI with neural data to reveal the hidden dynamics of cognition. Our platform bridges research and real-world solutions for healthcare, human-computer interaction, and cognitive enhancement.
- Interpretable models aligned with neuroscience
- Privacy-first pipelines for neuroimaging and signals
- Collaborations with leading labs and clinics
Neuroimaging Analytics
End-to-end pipelines for fMRI, EEG, and MEG with interactive insights.
Learn moreEthical AI Lab
Rigorous frameworks for trust, transparency, and neurodata stewardship.
Learn moreBrain-inspired Models
We translate cortical motifs into efficient ML architectures. Expect sparse coding, recurrence, and topographic constraints that yield robust generalization under limited data.
- Recurrent routing and attention for temporal reasoning
- Energy-efficient representations inspired by cortical sparsity
- Topographic embeddings aligned with neuroimaging data
Neuroimaging Analytics
End-to-end pipelines for fMRI, EEG, and MEG with interpretable maps and interactive reports powered by modern visualization.
- Artifact removal and harmonization across sites
- Contrastive models linking brain signals to behavior
- Explainers with uncertainty and causality hints
Ethical AI Lab
We embed ethics into the stack: privacy-first data flows, rigorous evaluation, and governance for responsible NeuroAI.
- Differential privacy & federated learning
- Secure multi-party computation
- Bias audits and risk assessments
- Model cards and data sheets
What our partners say
Dr. Lina Park
NeuroAI Lab, UCL
WaxBrain’s interpretable models set a new bar for science-grade AI. We translated weeks of analysis into minutes.
Alex Romero
CTO, Synaptic Health
Their privacy-first neurodata stack enabled multi-site collaboration without compromising patient trust.
Prof. Mei Chen
Cognitive Systems, MIT
A rare team combining rigorous neuroscience with product polish. The collaboration was seamless.
Trusted by forward-thinking institutions
From our blog
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Decoding thoughts: contrastive neuro-embeddings
We explore embeddings that align brain signals with language for interpretable readouts.
Federated fMRI with strong privacy guarantees
Techniques to learn across hospitals while preserving patient privacy.
Closing the loop: neuroadaptive interfaces
Design principles for interfaces that respond to cognitive state in real time.