Sabi raises $50M to build a wearable brain-computer interface that converts thoughts into prompts

Sabi Raises $50M for Wearable Brain-Computer Interface

Overview

Sabi, a Palo Alto startup, has raised $50 million to build a wearable brain-computer interface that converts thoughts into prompts. The device is a beanie, not a brain implant.

Technology

A hat with a lot going on underneath Sabi's flagship product is a beanie embedded with dense arrays of miniature EEG sensors. EEG, or electroencephalography, reads the brain's electrical activity from outside the skull, so nothing gets implanted. Sabi says the beanie packs between 70,000 and 100,000 miniature sensors, each about 1 mm in size. The goal is to decode internal thoughts into digital text or commands. Sabi's estimated decoding speed is around 30 words per minute.

Market and Funding

Who is writing the checks The $50 million round drew a recognizable lineup. Investors include Khosla Ventures, Accel, Initialized Capital and DST Global.

Product Development

A baseball cap variant is also in the pipeline, pitched as a more discreet option. Sabi plans to use the capital in two areas. The first is improving its hardware capabilities. The second is developing its proprietary 'Brain Foundation Model,' a large AI model trained to understand brain signals. Sabi claims the model is built on the world's largest neural decoding dataset, totaling approximately 100,000 hours of data collected from around 100 volunteers.

Timeline

From stealth to shipping in one year Sabi was founded around 2023. It emerged from stealth in mid-April 2026, around April 16, with plans to bring brain-computer interfaces into the consumer wearable market. The funding announcement came roughly six months later. Shipment of the product is anticipated by the end of 2026. Sabi is also emphasizing end-to-end encryption and has made commitments to external audits.

Comparison to Neuralink

Sabi is positioning itself directly against surgical brain-computer interfaces like Neuralink. Those systems require invasive procedures to place hardware inside the head. The tradeoff is signal quality. Reading the brain through the skull is harder than reading it from the inside, which is exactly why Sabi is stacking so many sensors and leaning on a large AI model to fill in the gaps.