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Teraki Raises $11 Million in Series A Funding

Teraki

Teraki today announced it has closed $11 million in Series A funding to address the problem of exploding data demand in tightly constrained electronics components such as those embedded in automotive systems. The oversubscribed financing follows the company’s strong momentum in customer engagements and expanded market opportunities, and brings the total capital invested to $16.3 million.

The company’s breakthrough AI and edge data processing software makes applications and algorithms run 10X more efficiently in cars and Internet of Things (IoT) devices, while preserving the data quality and accuracy required for training and running machine learning models. Teraki enables edge devices to do more without increasing hardware resource requirements and costs.

The round is led by Horizons Ventures, joined by strategic investors including a leading Japanese technology company; US-based State Auto Labs Fund – managed by Rev1 Ventures; Bright Success Capital; and Castor Ventures. Existing investors Paladin Capital Group and innogy Ventures also participated.

The investment will be used to accelerate Teraki’s current focus on the $395 billion automotive electronics market, as well as to expand into sectors facing a similar rise in data demands in tightly constrained computing and communications components, including IoT, drones, robotics and others. The company’s partnerships with Microsoft and Infineon highlight the relevance of Teraki software to these markets for leading cloud players and global producers of edge chipsets.

Gartner forecasts that 20.4 billion connected things will be deployed by 2020, opening opportunities for increased efficiencies through automation and autonomous control. However, IoT devices are typically small with constraints on battery life, CPU performance, data storage and communications bandwidth within the device and to the cloud. These challenges are similar to those encountered in the automotive industry. Teraki’s software enables these devices to do 10X more, communicate 10X more efficiently and accelerate AI and machine learning up to 10X faster.

“We will use these funds to propel Teraki into new areas outside of automotive with significant recurring revenues as clients start large scale deployments of our technology,” said Dr. Daniel Richart, CEO and co-founder of Teraki. “These funds will also enable us to fulfill demand from our existing automotive manufacturing and supplier customers for high volume production series orders.”

Jonathan Tam, from Hong Kong based Horizons Ventures, said: “We are impressed with what the talented team at Teraki has delivered and achieved. As sensors and devices continue to collect more data to enrich AI algorithms, efficient data processing will be a crucial part of the technology stack. We believe Teraki’s technology will become the backbone for the future of AI on the edge.”

Other uses of the funds include further growing the current team of 40 employees, expanding into the U.S. and Asia, and accelerating the product roadmap. As part of the expansion into Asia the company recently opened offices in Seoul and Tokyo.

Teraki has quickly proven itself as a leading innovator in Berlin’s rapidly expanding AI and Edge Computing space. Teraki has a number of engagements with automotive OEMs, Tier 1 suppliers and semiconductor customers.

Gibb Witham, Senior Vice President at Paladin Capital, said, “As early believers in Teraki, we are excited by the exceptional team of world-class AI talent that they’ve brought together and strong initial traction towards this huge market opportunity. We are excited to welcome a global syndicate of strategic investors in this next phase of growth for the company.”

Teraki will present its unique Intelligent Signal Processing product at CES 2020 in booth 9520, LVCC Northern Hall, January 7 – 10 in Las Vegas. There Teraki will demonstrate sensor fusion of LIDAR and camera streams, accurately detecting objects in real time on a low-powered computing device complying with the highest quality requirements for data collection in automotive.