AI-In-Sensor Processor Company AIStorm Secures $13.2 Million

By Noah Long ● February 13, 2019

AI-in-sensor processor company AIStorm has raised $13.2 million in Series A funding from Egis Technology, TowerJazz, Meyer Corporation, and Linear Dimensions Semiconductor. Egis Technology is a major biometrics supplier to handsets, gaming, and advanced driver-assistance systems (ADAS). TowerJazz specializes in image sensors for commercial, industrial, and medical markets. Meyer Corporation is a leader in food preparation equipment. And Linear Dimensions Semiconductor is a leader in biometric authentication and digital health.

“This investment will help us accelerate our engineering & go-to-market efforts to bring a new type of machine learning to the edge,” said AIStorm CEO David Schie in a statement. “AIStorm’s revolutionary approach allows implementation of edge solutions in lower-cost analog technologies. The result is a cost savings of five to ten times compared to GPUs — without any compromise in performance.”

AIStorm is aiming to solve the need for cost reductions and resolving security risks associated with transmitting large amounts of raw data from edge sensors. This is important because AI systems require information to be available in digital form before it can process data, but the sensor data is analog. AIStorm is able to process sensor data directly in the native analog form in real-time.

TowerJazz CEO Russell Ellwanger said that the reaction time saved by AIStorm’s approach “can mean the difference between AIStorm’s approach can mean the difference between an advanced driver-assistance system detecting an object and safely stopping versus a lethal collision.”

Egis Technology COO Todd Lin pointed out that AIStorm’s approach allows them to intelligently prune data from sensor streams in real time and keep up with massive sensor input tasks. Dr. Avi Strum, the SVP/GM of the sensors division of TowerJazz said that it makes sense to combine the AI processing with the imager and skip the costly digitization process.