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Lantronix Partners with Safe Pro to Develop Edge AI Solutions for Threat Detection

Lantronix partners with Safe Pro to co-develop Qualcomm-based edge AI solutions, enhancing drone threat detection capabilities while shares see a 34.96% rise in three months.

Lantronix Inc. (LTRX) has entered into a strategic partnership with Safe Pro Group, signing a Memorandum of Understanding and a Master Services Agreement to co-develop Qualcomm-based edge AI solutions aimed at enhancing real-time threat detection capabilities in drones and unmanned systems. This collaboration seeks to integrate Lantronix’s hardware with Safe Pro’s Object Threat Detection software, specifically designed for defense and security applications that require on-device processing without the need for constant cloud connectivity.

This latest agreement follows a strong performance by Lantronix, which has seen its share price increase by 34.96% over the past three months and a total shareholder return of 68.96% over the last year. Currently, shares are trading at $6.64, despite a recent decline of 2.35%. The significant price movements suggest that investor sentiment is increasingly optimistic about the company’s growth prospects.

Investors are now weighing whether Lantronix is undervalued at its current price point. The company’s recent revenue stands at approximately $118.3 million, with a reported net loss of $10.3 million. Analysts project a fair value of $7.88 per share, indicating that the stock may still hold potential for growth. However, the current price-to-sales (P/S) ratio of 2.2x exceeds the industry average of 1.9x and a fair ratio of 1.6x, implying that there may be less margin for error if future growth or profit margins fall short of expectations.

Additionally, Lantronix’s launch of EdgeFabric.ai, which features no-code edge AI workflow tools for cameras, drones, and industrial monitors, aims to deepen customer engagement and accelerate deployment cycles. This development is expected to expand the company’s mix of high-margin recurring software and services, enhancing net margins as software contributions rise beyond the current mid-single-digit percentage of total revenue.

Despite the positive narrative surrounding the company’s potential for higher-margin software and recurring revenue, analysts caution that the current projections depend heavily on the early-stage demand for drone technology and the adoption of AI SaaS solutions. Any slowdown in these sectors could pose challenges to the optimistic fair value assessment.

The prevailing analyst narrative indicates Lantronix as undervalued at its projected fair value of $7.88. However, with the current P/S ratio standing at 2.2x, the market appears to be pricing in a more cautious outlook compared to the bullish narrative provided by analysts. Investors are thus faced with a dilemma: should they trust the story of growth potential, or the metrics that reflect current valuations?

For those considering an investment in Lantronix, a review of its financial data alongside broader market conditions is advisable. The company’s strong growth over the past year could attract more investors, yet the underlying risks remain significant, particularly in technology sectors that are still finding their footing.

As the tech landscape continues to evolve, particularly in AI and edge computing, opportunities abound for investors willing to look beyond individual companies. Continuing to expand one’s view could reveal other high-growth tech stocks that align more closely with one’s investment goals and risk tolerance.

This article by Simply Wall St strives to provide an unbiased view based on historical data and analyst forecasts. It is essential for investors to conduct their own research and consider their financial circumstances before making investment decisions. Simply Wall St does not hold any positions in the stocks mentioned.

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Rachel Torres
Written By

At AIPressa, my work focuses on exploring the paradox of AI in cybersecurity: it's both our best defense and our greatest threat. I've closely followed how AI systems detect vulnerabilities in milliseconds while attackers simultaneously use them to create increasingly sophisticated malware. My approach: explaining technical complexities in an accessible way without losing the urgency of the topic. When I'm not researching the latest AI-driven threats, I'm probably testing security tools or reading about the next attack vector keeping CISOs awake at night.

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