AI firm BrainChip Holdings raises US$4.5M in private placement

Artificial intelligence (AI) and machine learning technologies developer BrainChip Holdings Ltd. has successfully raised AUS$6.0 million (US$4.5 million) through a share placement.

The placement, which was oversubscribed, was supported by BrainChip’s existing shareholders and new institutions with Foster Stockbroking acting as sole lead manager.

BrainChip will use the raised capital to support its ongoing operational expenses and expand its sales and marketing efforts for two key new products to be launched later this year.

“This capital raise will support the expansion of our sales and marketing efforts at an important time in our growth,” said Louis DiNardo, BrainChip’s president and CEO. “Our new products are an excellent extension of the work we have done with existing customers and will allow us to pursue large-scale deployments with a broad line of solutions serving multiple use cases.”

In September, the company plans to release its SNAPvision software product line — a first-of-its-kind solution that provides facial and pattern recognition solutions for Homeland Security and law enforcement efforts in anti-terrorism and crime prevention.

The SNAPvision software delivers the capabilities of a spiking neural network, including one-shot learning and high performance in low-light, low-resolution imaging environments.

The software will enable law-enforcement and intelligence agencies to rapidly conduct forensic and live-search across large video networks, acting as a force multiplier to expedite the detection of subjects of interest.

In the third quarter, the company expects to release the SNAPvision hardware accelerator card, which enable high-speed, high-density video analytic acceleration of multiple high-definition channels.

The card will reduce latency, increase throughput and lower the total cost of ownership for large-scale installations.

Article Topics

artificial intelligence  |  biometrics  |  BrainChip  |  facial recognition  |  investment  |  machine learning