Tibbling Technologies offers a brain‑inspired AI platform that learns from limited data and provides zero‑shot, domain‑generalized representations for complex, multimodal biological datasets. The platform includes specialized modules such as AnimalFormer for behavioral analysis, ExerAIde for multimodal sports diagnostics, and Segment AnyNeuron for automated neuron segmentation, enabling researchers in academia, hospitals, and biotech to accelerate data analysis without extensive retraining.
Funding
Funding not disclosed
Founders
Product
Problem
Life scientists rely on data analysis tools that were designed before modern AI, making it difficult to extract meaningful insights from complex, multimodal biological datasets. Conventional methods often require large amounts of labeled data and struggle to generalize across species, modalities, or experimental conditions.
Solution
Tibbling Technologies provides a brain‑inspired AI platform that learns efficiently from limited examples and generalizes across diverse biological contexts. By modeling computational principles of the neocortex, the platform enables zero‑shot and domain‑generalized representations, allowing researchers to apply a single model to varied datasets without extensive retraining. The suite includes specialized modules for tasks such as AAV enhancer discovery, behavioral analysis, multimodal diagnosis, and brain‑wide neuron segmentation. Results are delivered through automated pipelines that integrate multimodal sensing and neuromorphic compute, reducing the need for manual feature engineering and accelerating hypothesis testing. The platform is positioned as a foundational tool for academic labs, research hospitals, and biotech companies seeking AI that aligns with the complexity of biology.
Target Audience
Primary customers are academic researchers, research hospitals, and biotechnology firms that need advanced AI tools to analyze complex, multimodal biological data.
Features
- Zero‑shot learning via a soft Winner‑Takes‑All approach for domain‑generalized representations
- AnimalFormer module for AI‑powered behavioral analysis to improve animal welfare and experimental productivity
- ExerAIde for multimodal diagnosis supporting sports performance optimization and personalized rehabilitation
- Mice‑to‑Machines framework that extracts neural representations from visual cortex to enable cross‑species domain generalization
- Segment AnyNeuron tool for automated, brain‑wide segmentation of neurons across diverse transgenic mouse lines
- Multimodal Sensing architecture that combines neuromorphic sensors with compute‑efficient transformers
- Brain Mapping capability providing domain‑agnostic 3D registration across species and imaging modalities
- Regulating NeuroAI component that enforces embodied efficiency and technical assurance for brain‑inspired computation