Nano Dimension’s (“Nano”) DeepCube Product (“DC-AI”) - First Time Under Commercial Contracts – Generating Revenue Independently Beyond Its Integration Into Nano’s 3D Printers

Rhea-AI Summary

Nano Dimension has made progress in commercializing its AI services by making its technology available for use by external customers. The company has signed an agreement with a multinational electronics company and is in discussions with other industrial and advanced manufacturing companies. The use cases vary but often focus on improving processes and increasing throughput and yield. Nano Dimension's strategy is based on deep learning-based AI, which has shown significant improvements for its additive manufacturing systems.

Positive

• Nano Dimension has signed an agreement with a large multinational electronics company to leverage its deep learning-based AI technology.
• The company is in discussions with several leading industrial and advanced manufacturing companies for the commercial use of its DeepCube technology.
• Improving throughput and yield are of the utmost importance for these companies, and even slight enhancements can lead to large financial upsides.

Negative

• None.

First Success in Nano’s Program to Financially Leverage Its DC-AI’s Deep Learning Innovations By Selling Into International Conglomerates

Waltham, Mass., July 05, 2023 (GLOBE NEWSWIRE) -- Nano Dimension Ltd. (Nasdaq: NNDM, “Nano Dimension” or the “Company”), a leading supplier of Additively Manufactured Electronics (“AME”) and multi-dimensional polymer, metal & ceramic Additive Manufacturing (“AM”) 3D printers, announced today that it has made notable progress in accelerating its plans to commercialize the industrial artificial intelligence (“AI”) services of its in-house DeepCube Group by making its propriety technology available for use by external customers.

Nano Dimension has signed an agreement with a large multinational electronics company to leverage DeepCube’s deep learning-based AI technology. The Company has also entered a memorandum of understanding (“MoU”) with another international industrial company and is in the latter stages of discussions with several more leading industrial and advanced manufacturing companies for the commercial use of its DeepCube technology.

While the use cases that are contracted for or being discussed vary by customer, they are often around improving the efficacy of processes through some combination of in-line or instantaneous analysis of images and/or data. For the cases at hand, improving throughput and yield are of the utmost importance, and even slight enhancements can translate into large financial upsides.

Nano Dimension has based much of its strategy around the application of deep learning-based AI. The Company acquired DeepCube twenty-six months ago and has since leveraged its technology and its leading group of data scientists to drive improvements for its proprietary additive manufacturing systems. After seeing the improvements that deep learning-based AI for industrial applications could create, Nano Dimension explored bringing this technology directly to clients for their own use cases, and it has been well-received.

Yoav Stern, Chairman and Chief Executive Officer of Nano Dimension, commented, “We are pleased to see results so quickly after being led by a clear and present “pull” from the market. Fortunately, customers are demanding DC-AI Deep Learning Engine for specific and various applications, beyond our adaptation of it to Additive Manufacturing.

While AI has been the topic of much conversation lately, it is hard to imagine a greater set of applications for this unique technology than the opportunities we are discussing with a range of top-tier customers. The nature of their businesses and the problems they face means that DC-AI can bring notable improvements to their products and services, while also translating into a better bottom-line.”

About Nano Dimension

Nano Dimension’s (Nasdaq: NNDM) vision is to transform existing electronics and mechanical manufacturing into Industry 4.0 environmentally friendly & economically efficient precision additive electronics and manufacturing – by delivering solutions that convert digital designs to electronic or mechanical devices - on demand, anytime, anywhere

Nano Dimension’s strategy is driven by the application of deep learning based AI to drive improvements in manufacturing capabilities by using self-learning & self-improving systems, along with the management of a distributed manufacturing network via the cloud.

Nano Dimension serves over 2,000 customers across vertical target markets such as aerospace & defense, advanced automotive, high-tech industrial, specialty medical technology, R&D and academia. The company designs and makes Additive Electronics and Additive Manufacturing 3D printing machines and consumable materials. Additive Electronics are manufacturing machines that enable the design and development of High-Performance-Electronic-Devices (Hi-PED®s). Additive Manufacturing includes manufacturing solutions for production of metal, ceramic, and specialty polymers based applications - from millimeters to several centimeters in size with micron precision.

Through the integration of its portfolio of products, Nano Dimension is offering the advantages of rapid prototyping, high-mix-low-volume production, IP security, minimal environmental footprint, and design-for-manufacturing capabilities, which is all unleashed with the limitless possibilities of additive manufacturing.

For more information, please visit www.nano-di.com.

Forward Looking Statements

This press release contains forward-looking statements within the meaning of the “safe harbor” provisions of the Private Securities Litigation Reform Act of 1995 and other Federal securities laws. Words such as “expects,” “anticipates,” “intends,” “plans,” “believes,” “seeks,” “estimates,” and similar expressions or variations of such words are intended to identify forward-looking statements. For example, Nano Dimension is using forward-looking statements in this press release when it discusses Financially Leverage Its DC-AI’s Deep Learning Innovations by selling to external customers and the opportunities it is discussing with a range of top-tier customers, and that DC-AI can bring notable improvements to their products and services, while also translating into a better bottom-line. Because such statements deal with future events and are based on Nano Dimension’s current expectations, they are subject to various risks and uncertainties. Actual results, performance, or achievements of Nano Dimension could differ materially from those described in or implied by the statements in this press release. The forward-looking statements contained or implied in this press release are subject to other risks and uncertainties, including those discussed under the heading “Risk Factors” in Nano Dimension’s annual report on Form 20-F filed with the Securities and Exchange Commission (“SEC”) on March 30, 2023, and in any subsequent filings with the SEC. Except as otherwise required by law, Nano Dimension undertakes no obligation to publicly release any revisions to these forward-looking statements to reflect events or circumstances after the date hereof or to reflect the occurrence of unanticipated events. References and links to websites have been provided as a convenience, and the information contained on such websites is not incorporated by reference into this press release. Nano Dimension is not responsible for the contents of third-party websites.

NANO DIMENSION INVESTOR RELATIONS CONTACT

Investor Relations | ir@nano-di.com

FAQ

What progress has Nano Dimension made in commercializing its AI services?

Nano Dimension has made notable progress in accelerating its plans to commercialize its AI services by making its technology available for use by external customers.

What is Nano Dimension's strategy based on?

Nano Dimension's strategy is based on deep learning-based AI, which has shown significant improvements for its additive manufacturing systems.

What are the use cases for Nano Dimension's DeepCube technology?

The use cases vary by customer but often focus on improving processes and increasing throughput and yield.