Neuraffica builds biological computing systems that reduce AI energy cost. We combine neurons, neurotechnology, and AI to create faster, more efficient alternatives to today’s compute infrastru
Current Status
-algorithmic demos in preparation,
-technical & feasibility research done,
-incorporated, team assembled,
-provisional patent filed Nov 2025
-proprietary data owned
-track of publication and expertise in the technical domains
-market fit research done
Problem or Opportunity
AI is architecturally not designed to be energy-efficient, and further AI adoption and progression are now limited by the supply chain of data centers, silicon chips, and energy. The AI infrastructure market needs multi-billion-dollar investments just to sustain current demand.
Solution (product or service)
We provide a new computing alternative: cheaper and more energy-efficient. Using real neuronal cells (STEM cells) on a chip, we are rebuilding the whole AI stack using 100x +++ more energy-efficient solutions. Starting from products that seamlessly integrate into the current market, we optimize: pre-training (using data produced at biocomputer), inference algorithms (using design patterns produced by biocomputer), finishing at AI training done entirely on biocomputer (GPT2 model training 111h to 25 min, 300W to 3W).
Business model
B2B
selling to enterprises with significant spending on AI infrastructure (~700 companies): robotic and physical AI companies, hyperscalers, data handlers
