Ladies and gentlemen, thank you for standing by. Welcome to GSI Technology's Third 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, January 27th, 2022, at the request of GSI Technology. Hosting the call today is Lee-Lean Shu, the company's Chairman, President, and Chief Executive Officer. With him are Douglas Schirle, Chief Financial Officer, and Didier Lasserre, Vice President of Sales. I would now like to turn the conference over to Mr. Shu. Please go ahead, sir.

Good afternoon and thank you for joining us to review our Fiscal Third Quarter 2022 Financial Results. Our third quarter revenue grew year-over-year by 19% due to increased order from SRAM customer base, including network and telecom, military and defense, as well as automotive, medical, and test and measurement sectors. The increase in orders from other customers offset a lower order from Nokia in the quarter. Gross margin improved by 800 basis points year-over-year, reflecting our ability to manage our near-term supply chain challenges and increased costs. Our lead loss narrowed year-over-year by 12% and we ended the quarter with $48.1 million in cash, cash equivalents, and short-term investments. We continue to prioritize the allocation of our capital on R&D for the APU, which includes the software and API development for Gemini-I and the table for Gemini-2. The software development team continues to extend our library of algorithms and the API for all target applications in search. In February, we plan to release our Compilers stack, and Didier will provide an overview of this in his section. At the end of calendar 2021, we announced that GSI was among the leaders in the Billion-Scale Approximate Nearest Neighbor Search Challenge. We were encouraged by this outcome. The results showed that the APU technology and the software performed on par with prominent industry leaders in AI, all with much broader resources than GSI. Contests teach us a lot about our 3D development of APU and how we can improve our performance. Contests like beginning and end market challenges are also effective ways to launch GSI's profile in our industry and among potential customers. This contest parlors highlight all these capabilities and increase awareness of our APU's unique value propositions. Last year, our first-place win in the challenge led to our introduction to IAI/Elta, who engaged with GSI to develop a SAR image processing acceleration system using the APU and our software. Elta has provided funding to build the SAR system based on APU technology. They will grant an exclusive perpetual license for all the fast SAR algorithms to GSI to allow GSI to sell a SAR system, including the algorithm to other customers. Assuming that the POC is successful, Elta will deploy the system in volume. The GSI team continues to build a pipeline of customer engagement and increase our POC activity for the APU. In addition to Elta's SAR project, we are in discussions with several organizations to engage in POC for a variety of use cases for search applications we are testing. Current POC engagements include indexing medical images and text, encrypted communication, and natural language processing. The prime contractor is interested in testing for military and defense applications. We also have a couple more agencies considering the APU for object detection and facial recognition. We anticipate that a portion of this POC will move to design wins and eventually to production. A few years back, once we had the Gemini-I chip available for testing, we made a strategic decision to pursue search instead of the training and inference markets, which are already filled with large, well-funded competitors. The APU performed significantly better in search applications, and we decided to target our resources to develop that market. This has proven to be a good decision, as we are now seeing search as a potentially large end market. We recognize that the APU works very efficiently with a trained database to rapidly search and deliver results, with low-latency, low-power consumption, and a scalable configuration. Accuracy, a smaller footprint, lowering the total cost of ownership, being space-ready, and reducing power consumption are key differentiators for the APU. We remain committed to our strategy and dedicated our capital to deliver the best technology for the live recording search market. Supply chain constraints continue to impact our order fulfillment. While there has been some improvement, the situation remains fluid. We have passed on some of the price increases and have factored this into our planning. However, we do not expect significant relief from these concerns before the end of 2022. We have increased our operational focus on managing the supply chain to fulfill existing orders for the upcoming quarters, and we will provide our outlook for the fourth quarter in the prepared comments. This year will be crucial in demonstrating the feasibility of our groundbreaking APU technology. Our less important milestones are the release of the Compiler Stack in February. This release shows a sale customer adoption of our groundbreaking technology. We are in early stages engaging with customers who recognize the APU's potential for their applications. The Compiler Stack should help us grow our pathway. It is an exciting time for GSI, and our team is focused on achieving our goals for current customer engagement while continuing to build our pipeline for new opportunities. Now I will hand the call over to Didier, who will discuss our business performance further. Please go ahead, Didier.

Thank you, Lee-Lean. As Lee stated, we have new customer engagements in multiple applications ranging from e-commerce to military and defense for various use cases. In our approach to the search market, we are pursuing opportunities that align with the applications we feel the APU is best suited. Right now, our team is seeding the field, and we fully expect that some of this will bear fruit. Our approach to supporting these customer engagements depends on the end-users' needs. For some, we loan them a board to demo. Others have access to our Sunnyvale data center to run their models, and then some have purchased some boards. Each of these engagements target unique market applications and the ultimate size of each opportunity may vary. Since many are in the early stages of development, it is challenging to measure. That being said, they are all of sufficient size to merit allocating our resources. Today, we are working with universities with unique applications, with broad market opportunities, and we also have prime contractors that could eventually turn into large orders, as well as a government agency evaluating the APU for border security. There's also an e-commerce company looking at the APU for natural language processing. You can see why we're excited about these engagements, as they could potentially develop into customers and growth markets. Our objectives are to make the POCs as successful as possible for each entity, expecting a portion to move to design wins and eventually to production. As part of GSI's strategy for the AI and HPC or High-Performance Computing acceleration market, we will soon be releasing an APU Compiler Stack. This release will deliver the environment for software and AI developers to write full applications using C for our Leda-E and Leda-S PCIe boards. The release will include example applications and training materials. Customers that need specific use case algorithms can edit our large collection of vector library functions and write their APU fragments in Python using our low-level product. Achieving the APU Compiler Stack milestone should accelerate customer adoption and is one of the most important steps in front of us to move the APU to the next level. As I mentioned earlier, the GSI team has been busy creating APIs for search workloads like image indexing, object recognition, natural language processing, as well as HPC workloads in the enterprise, and real-time applications like SAR, ATR, and signal classification at the edge. We have documented that the APU technology can offer enterprise AI capacity in both edge standalone and server environments to support that migration. The APU compiler stack is a powerful tool for researchers and developers that promises to significantly expand the market applications for our non-Von-Neumann processor. To help build a pipeline, GSI will introduce a series of training seminars to support the customization of our APIs for specific applications. The APU technology is available in a PCIe board for enterprise and edge server applications, capable of searching tens of millions of vectors per board. The platform is highly scalable, allowing us to connect unlimited boards installed in servers. The hardware capability can also function as a cloud-based software-as-a-service for open search and elastic search acceleration. Once we launch the Compiler Stack, we plan to provide more details in a press release. Let me switch now to the customer and product breakdown for the third quarter. In the third quarter of Fiscal 2022, sales to Nokia totaled $1.9 million or 24% of revenues compared to $2.8 million or 42% of revenues in the same period a year ago, and $1.9 million or 23.8% of net revenues in the prior quarter. Military defense sales were 27.1% of third quarter shipments compared to 26.0% of shipments in the comparable period a year ago, and 27.4% of shipments in the prior quarter. SigmaQuad sales were 40.5% of third quarter shipments compared to 62% in the third quarter of fiscal 2021 and 52.4% in the prior quarter. In closing, as Lean mentioned, we have ongoing challenges with supply chain constraints, with substrate lead times extending over a year. Overall, the impact of increased wafer prices, assembly labor costs, rising substrate prices, and expediting charges has led us to raise prices to all of our customers in December.

Thank you, Didier. We reported a net loss of $4.6 million or $0.19 per diluted share on net revenues of $8.1 million for the third quarter of Fiscal 2022, compared to a net loss of $5.2 million or $0.22 per diluted share on net revenues of $6.8 million for the third quarter of Fiscal 2021, and a net loss of $4.6 million or $0.19 per diluted share on net revenues of $7.8 million for the second quarter of Fiscal 2022. Gross margin was 55.3% compared to 47.3% in the prior-year period and 53.6% in the preceding second quarter. The changes in gross margin were primarily due to changes in product mix sold for the three periods. Total operating expenses in the third quarter of Fiscal 2022 were $9 million compared to $8.3 million in the third quarter of Fiscal 2021 and $8.7 million in the prior quarter. Research and Development expenses were $6.2 million compared to $5.7 million in the prior-year period, and $5.9 million in the prior quarter. Selling, general, and administrative expenses were $2.8 million in the quarter ending December 31, 2021, compared to $2.6 million in the prior-year quarter, and $2.8 million in the previous quarter. The third-quarter fiscal 2022 operating loss was $4.5 million compared to $5.2 million in the prior-year period, and $4.5 million in the prior quarter. The third quarter fiscal 2022 net loss included net interest and other expenses of $15 thousand and a tax provision of $64 thousand, compared to $25 thousand net interest and other income and a tax provision of $90,000 for the same period a year ago. In the preceding second quarter, net loss included interest and other expenses of $8,000 and a tax provision of $42,000. Total third quarter pre-tax stock-based compensation expense was $740,000 compared to $693,000 in the comparable quarter a year ago and $716,000 in the prior quarter. At December 31st, 2021, we had $48.1 million in cash, cash equivalents, and short-term investments, and $3.4 million in long-term investments compared to $54 million in cash, cash equivalents, and short-term investments, and $5.8 million in long-term investments at March 31, 2021. With no debt, working capital was $49.9 million as of December 31, 2021 versus $56 million at March 31, 2021. As of December 31, 2021, stockholders’ equity was $66.8 million compared to $75.6 million as of the end of the fiscal year on March 31, 2021. Supply chain constraints have impacted our ability to fill all of our orders. While there has been some improvement, the situation remains fluid, and we do not expect significant relief from these constraints before the end of the calendar year 2022. Given these constraints, current expectations for the upcoming fiscal fourth quarter are net revenues in the range of $7.5 million to $8.5 million, with gross margin of approximately 54% to 56%.

At this point, we'll open the call to Q&A.

Hi guys. In terms of the orders that you have not been able to fulfill, are those gone, do those go to someone else, or is that backlog that's building up?

The majority of the backlog has built up. While some orders may have been lost due to multiple sources, this represents a very small percentage of our business. Most of the backlog remains and will be fulfilled later.

Got you. Okay. And then can you just give us a quick update on the Rad-Tolerant efforts?

Sure. So the Rad-Tolerant, we spoke of in the past, we've had some shipments out. In fact, on some Rad-Hard as well. And so some of those we are in the prototype stages. We're waiting for them to do their testing, as it takes some time. What we didn't discuss is that in this quarter, we actually booked another prototype for a Rad-Hard device. So we have a Rad-Hard on the books now that will ship hopefully this quarter. And again, it's for prototyping, for a satellite that will go into production in a couple of years. So we're starting to still see some prototyping. As we mentioned in the past, the Rad-Hard is still a bit of a challenge because some of the meetings we still can't have. But the Rad-Tolerant, we're definitely seeing traction there.

Okay. And then there was the issue of actually getting some of these parts into space before some people would look at using them. Where are we on getting a ride?

Right. Exactly. So that's called heritage. Once you get heritage, which is proving that your parts work in space, it certainly makes our job with most customers very easy. In fact, we've had several customers say they're going to wait for heritage before they move forward. Some of the parts that we shipped in, I want to say, summer of last year, maybe late summer, were going to be our first parts that can get into space. Those are being put on the satellites being assembled now, so we're hoping for a launch sometime this year. And while we certainly don't have control over when that happens, we are following up with that customer often, and right now it's sometime in calendar 2022 that it will be in space. If you recall, that was a demo system for a possible constellation in the future, but that will give us our first heritage, and we're hoping that's this year.

All right, thanks.

Okay, at this time, I'm not seeing any more questions. I'd like to pass it back over to Mr. Shu for closing remarks.

Thank you all for joining us. We look forward to speaking with you again when we're waiting for our fourth quarter and full-year fiscal 2022 results. Thank you.

This concludes today's conference. You may disconnect your lines at this time. Thank you for your participation, and have a great day.