GSI Technology, Inc.

Good day, ladies and gentlemen, and thank you for standing by. Welcome to GSI Technologies' first quarter fiscal 2022 results conference call. At this time, all participants are in a listen-only mode. Later, we will conduct a question and answer session. At that time, we will provide instructions for those interested in entering the queue for the Q&A. Before we begin today's call, the company has requested that I read the following Safe Harbor statement. The matters discussed in this conference call may include forward-looking statements regarding future events and the future performance of GSI technology that involve risks and uncertainties that could cause actual results to differ materially from those anticipated. These risks and uncertainties are described in the company's Form 10-K filed with the Securities and Exchange Commission. Additionally, I have also been asked to advise you that this conference call is being recorded today, July 29, 2021, at the request of GSI Technology. Hosting the call today is Leland Hsu, the company's chairman, president, and chief executive officer. With him are Douglas Shirley, chief financial officer, and Didier Lassere, vice president of sales. I would now like to turn the conference over to Mr. Hsu. Please go ahead, sir.

Good afternoon, everyone, and thank you for joining us to review our first quarter 2022 financial results. First quarter revenue improved year over year, and subscribe sequentially due to higher sales to Nokia, our largest customer. There was increased demand for our Sigma Quad products, which improved growth margin and narrowed our operating loss. We ended the quarter with over $55 million of liquid assets, more than sufficient funds to achieve our goals of building successful business for new products. The net revenues from our legacy S1 business continue to support our new product categories, primary radiation-tolerant devices, and the Gemini APU solutions. We shipped our first radiation-tolerant devices in the first quarter and increased our better customer engagement for Gemini One system. Our effort to build market recognition of this new product category yield several promising results in the first quarter. First, winning first place in the market challenge has opened the door to a ready prime contractor with whom we successfully demonstrated Gemini's overall value proposition for synthetic aperture radar or SAR applications leading to a proof of concept engagement for SAR systems. The partnership with Space Micro for the Phase One NASA Small Business Innovation Research, or SBIR program, has gotten underway. We expect to submit a Phase Two proposal to develop an optimum real-time data sorting influence processing unit for Earth Observation Mission later this year. In the third, In the first quarter, we ship our first radiation-tolerant X-ray devices, an essential step in getting space heritage for our radiation-hardened and tolerant devices. Didier will provide details on our progress in each of these new engagements in his remarks to follow. Last week, AWS launched OpenSearch 1.0, the first production-ready versions of OpenSearch, a project that AWS first introduced in April 2021. The OpenSearch project is a community-driven, open-source search and analytics suite derived from open-source Elasticsearch and Kibana Elasticsearch data visualization dashboard software. Since the spring, we have been working with AWS on this project demonstrating GSS Elasticsearch KAM plugin. Elasticsearch was initially designed as a text and document search engine. The Gemini Elasticsearch KAM plugin or extension extends Elasticsearch's ability to search beyond just text. The plugin opens the door to other data types like image, video, audio, any data type that can be represented as a compact, semantically rich numerical vector. Vectors can be used to search for the most similar items or layers to a query. They can accelerate multiple applications, such as a visual search, face recognition, natural language processing, and the recommendation systems. Our extension provides a high-performance, low-latency, low-power, billion-scale vector similarity search solution that allows users to combine traditional text filters with vector search queries. Here's the problem we solve. Core Elasticsearch uses a match-all functionality which makes it too slow to handle the large-scale initial retrieval step in the vector terminology search pipeline. This limits core Elasticsearch to scoring documents on a small, filtered set of vectors. Instead, using an exhaustive match-all search, the GSF plug-in performs an approximate nearest-level all KNN vector terminology search. This allows the GSI extension to scale to billions of documents and handle the essential initial retrieval step in a search pipeline. Multi-model search, where image and text can combine to form a powerful search, is a rapidly emerging trend. Online fashion and home design use multi-model search because they really heavily Visual search, since style is often difficult to describe using text. In addition to visual search, text search is also required because production, product information like item description, category, and brand is generally used to filter the return result as part of the visual search. A solution that allows for multi-model search is needed. Open source search. Library do not handle multi-modal search well. The popular open source vector search library such as FACE and NMS library are good at the nearest-level vector search but lack support for efficient data filtering. For example, it could be difficult to use textual filters to filter the results previously returned from the nearest-level vector search. GSI solved this problem with its Elasticsearch plugin by allowing multi-model searches to be performed efficiently and effectively. Our extensions provide a high-performance, low-latency, low-power solution that combines traditional Elasticsearch text filters with vector search queries, solving the imaging and text search problem. and our solution is compelling because we require fewer resources for a better outcome. After successfully proving that the Gemini APU significantly accelerates vector search performance, Amazon OpenSearch Service included GSI as one of its service partners in the project. AWS recently released version 1.0 of OpenSearch for users of Elasticsearch and developers building products and services based on Elasticsearch. AWS has select partners that offer software and extensions that support OpenSearch in various applications, like our Elasticsearch KNN plugin that expands Elasticsearch's ability to search beyond just text. We are excited to be a part of this team. We are in the early stage of developing this opportunity and we still have a lot of work to do. We still need to finalize business model and are setting up a data center in Silicon Valley with the Gemini APU server in the GSI cloud to connect to the AWS data center nearby. Once the setup is complete and successfully demonstrated, we could now restore more servers and get better users by year end. And if all goes well, open up to all customers in calendar 2022. Long-term, we may install Gemini APU servers at data centers in many locations around the world. The first quarter has been productive for GSI. My team here in California, as well as our teams in Israel and Taiwan, are all highly committed to our goal of landing customers and building successful business. for our radiation-tolerant devices and the Gemini APU. We are progressing and remain optimistic that we will be successful in executing our long-term strategy. I sincerely thank you for your support as a fellow GSI shareholder. Now I hand the call over to Didi, who will discuss our business performance in further detail. Please go ahead, Didi.

Thank you, Lilien. I would like to provide an update on two product categories, our radiation-tolerant or RAD-tolerant chip that shipped in the June quarter and our progress on the APU and government projects. Last quarter, we shipped our first RAD-tolerant SRAM for an initial satellite flight expected to occur at the end of this calendar year. If the initial flight is successful, then a larger satellite constellation build is expected to start later in calendar 2022. We now anticipate a companion satellite project that will use the same class of rad-tolerant SRAM. This is a substantial opportunity for us and also brings the key benefit of establishing heritage for our rad-hard and rad-tolerant SRAMs in space. We anticipate that having heritage will be a growth catalyst for this product category. Shifting gears to the APU, As we previously announced, we partnered with Space Micro for our Phase 1 NASA SBIR program. We believe this project can serve as a catalyst for APU sales in this sector. In this project, the APU will function as the main engine for a single-board computer in space, which for this project is being referenced as an IPU, or an Inference Processing Unit. Phase one is officially underway after the initial kickoff meeting and is expected to be completed before year end. The next step is to submit a phase two proposal, which will probably happen in early calendar 2022. This is an exciting opportunity to put APU in the hands of multiple government agencies and prime contractors for space applications. Lastly, another exciting APU development is the outcome of winning the MAFAD challenge at the end of last year. Since then, Moffat has gotten to know GSI, and the team has had the opportunity to work on our APU with Moffat to demonstrate the scope of functionality of the device. Notably, we have demonstrated the APU's capability to perform SAR operations that our APU functionality exceeds that of the CPU and the GPU by a factor, in some cases, 100 times better, including lower power and lower overall system cost. As a result, we are now working with an Israeli defense prime contractor to deliver proof of concept servers to perform SAR operations. We expect to deliver the servers in early calendar 2022. If the effort is successful, we hope to leverage the success into other projects. Shifting to the sales breakdown for the first quarter of fiscal 2022, sales to Nokia were 3.8 million or 42.7% of net revenues, compared to $1.8 million or 26.9% of net revenues in the same period a year ago and $2.8 million or 36.5% of net revenues in the prior quarter. First quarter fiscal 2022 net revenues include orders for buffer stock shipped to Nokia amounting at approximately $1.1 million that were made in anticipation of continued market tightness. Military defense sales were 20.1% of first quarter shipments compared to 30.1% of shipments in the comparable period a year ago and 22.5% of shipments in the prior quarter. Sigma quad sales were 63.6% of first quarter shipments compared to 46.3% in the first quarter of fiscal 2021 and 52.9% in the prior quarter. But now I'd like to hand the call over to Doug. Go ahead, Doug.