Mobix Labs Partners with National Railroad Carrier to Advance AI-Driven Rail Safety
Mobix Labs (Nasdaq: MOBX) has announced a collaboration with a national railroad carrier to develop AI-powered safety technologies for rail infrastructure monitoring. The company's Wireless Division, RaGE Systems, is developing multi-sensor systems to assess wooden rail tie conditions.
The project's current phase involves designing sensor arrays for track vehicles that will collect detailed rail tie data, analyzed using proprietary reconstruction algorithms and AI models. The program, extending into early 2026, aims to create a train-mounted solution for full-speed assessments.
The technology targets the U.S. rail network's 140,000 miles of track and 450 million rail ties, addressing the annual replacement of approximately 16 million ties.
Mobix Labs (Nasdaq: MOBX) ha annunciato una collaborazione con un operatore ferroviario nazionale per sviluppare tecnologie di sicurezza basate sull'intelligenza artificiale per il monitoraggio dell'infrastruttura ferroviaria. La divisione Wireless dell'azienda, RaGE Systems, sta mettendo a punto sistemi multisensore per valutare lo stato delle traverse in legno.
La fase attuale del progetto prevede la progettazione di array di sensori da installare su veicoli della linea, in grado di raccogliere dati dettagliati sulle traverse, poi analizzati con algoritmi proprietari di ricostruzione e modelli di IA. Il programma, che proseguir脿 fino ai primi mesi del 2026, punta a realizzare una soluzione montata sui convogli per valutazioni a piena velocit脿.
La tecnologia 猫 destinata alla rete ferroviaria statunitense di 140.000 miglia di binari e a circa 450 milioni di traverse, con l'obiettivo di gestire la sostituzione annuale di circa 16 milioni di traverse.
Mobix Labs (Nasdaq: MOBX) ha anunciado una colaboraci贸n con un operador ferroviario nacional para desarrollar tecnolog铆as de seguridad impulsadas por IA para el monitoreo de la infraestructura ferroviaria. La divisi贸n Wireless de la compa帽铆a, RaGE Systems, est谩 creando sistemas multisensor para evaluar el estado de las traviesas de madera.
La fase actual del proyecto incluye el dise帽o de matrices de sensores para veh铆culos de v铆a que recopilar谩n datos detallados de las traviesas, analizados mediante algoritmos de reconstrucci贸n patentados y modelos de IA. El programa, que se extender谩 hasta principios de 2026, busca crear una soluci贸n montada en trenes para evaluaciones a velocidad completa.
La tecnolog铆a se dirige a la red ferroviaria de EE. UU. de 140.000 millas de v铆as y a 450 millones de traviesas, abordando la sustituci贸n anual de aproximadamente 16 millones de traviesas.
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Mobix Labs (Nasdaq: MOBX) a annonc茅 une collaboration avec un op茅rateur ferroviaire national pour d茅velopper des technologies de s茅curit茅 assist茅es par IA destin茅es 脿 la surveillance des infrastructures ferroviaires. La division Wireless de la soci茅t茅, RaGE Systems, met au point des syst猫mes multisenseurs pour 茅valuer l'茅tat des traverses en bois.
La phase actuelle du projet consiste 脿 concevoir des r茅seaux de capteurs pour des engins de voie qui collecteront des donn茅es d茅taill茅es sur les traverses, analys茅es 脿 l'aide d'algorithmes de reconstruction propri茅taires et de mod猫les d'IA. Le programme, qui se poursuivra jusqu'au d茅but de 2026, vise 脿 cr茅er une solution embarqu茅e sur train pour des 茅valuations 脿 pleine vitesse.
La technologie cible le r茅seau ferroviaire am茅ricain de 140 000 miles de voies et environ 450 millions de traverses, en s'attaquant au remplacement annuel d'environ 16 millions de traverses.
Mobix Labs (Nasdaq: MOBX) hat eine Zusammenarbeit mit einem nationalen Bahnbetreiber angek眉ndigt, um KI-gest眉tzte Sicherheitstechnologien f眉r die 脺berwachung der Bahninfrastruktur zu entwickeln. Die Wireless-Sparte des Unternehmens, RaGE Systems, entwickelt Multisensor-Systeme zur Bewertung des Zustands von Holzschwellen.
Die aktuelle Projektphase umfasst die Auslegung von Sensorarrays f眉r Gleisfahrzeuge, die detaillierte Daten zu Schwellen erfassen, welche mittels propriet盲rer Rekonstruktionsalgorithmen und KI-Modellen analysiert werden. Das Programm l盲uft bis Anfang 2026 und zielt darauf ab, eine zugwagenmontierte L枚sung f眉r Bewertungen bei voller Geschwindigkeit zu schaffen.
Die Technologie richtet sich an das US-Eisenbahnnetz mit 140.000 Meilen Gleis und etwa 450 Millionen Schwellen und adressiert den j盲hrlichen Austausch von rund 16 Millionen Schwellen.
- Development of innovative AI-powered technology for rail infrastructure monitoring
- Targeting a large market with 450 million rail ties and 16 million annual replacements
- Potential for cost reduction and safety enhancement in rail maintenance
- Opportunity for global market expansion in railroad infrastructure
- Extended development timeline into early 2026 before potential commercialization
- Technology still in early development phase without proven commercial success
Insights
Mobix Labs' AI-driven rail tie monitoring partnership opens a significant maintenance optimization market within the $450M+ annual rail infrastructure space.
This partnership positions Mobix Labs to address a substantial market opportunity in rail infrastructure maintenance. With 450 million rail ties across the U.S. rail network and 16 million replacements annually, the potential addressable market is significant. The wooden tie inspection challenge represents a perfect application for AI and advanced sensing technology.
The technical approach is particularly noteworthy. Mobix is developing sensor arrays for slow-moving vehicles initially, with plans to create systems that function at full operational speed. This progressive development strategy reduces technical risk while still advancing toward a commercially viable solution. The company's expertise in reconstruction algorithms, sensor fusion, and AI models positions them well for this specialized application.
The timeline extending into early 2026 indicates this is still in development rather than immediate commercialization. However, this phased approach demonstrates methodical technology validation before scaling. The ultimate goal of a self-contained, train-mounted solution that works at full operational speeds would provide significant efficiency advantages over current inspection methods.
The real value proposition lies in the economic benefits for railroad operators: potentially reducing the $450M+ spent annually on tie replacement through better predictive maintenance, extending asset lifecycles, and enhancing safety through more consistent monitoring. If successful, this solution could be marketed globally, significantly expanding Mobix Labs' total addressable market in industrial applications.
IRVINE, Calif., Aug. 21, 2025 (GLOBE NEWSWIRE) -- Mobix Labs, Inc. (Nasdaq: MOBX), a leading provider of advanced connectivity and sensing solutions, today announced that its Mobix Labs Wireless Division, RaGE Systems, is collaborating with a national railroad carrier to develop next-generation safety technologies for the rail industry.
The initiative focuses on deploying AI-powered multi-sensor systems capable of imaging and classifying the physical condition of wooden rail ties. In the current phase, Mobix Labs Wireless is designing a sensor array that can be mounted onto slow-moving track vehicles to capture detailed data on ties and rail beds. The collected information will be analyzed using the company鈥檚 proprietary reconstruction algorithms, sensor fusion techniques, and AI models to determine the health classification of each rail tie under a wide range of conditions.
This phase of the program, expected to continue into early 2026, will identify the most effective sensor configuration and AI approach to be scaled for broader deployment. The ultimate goal is to deliver a self-contained, train-mounted solution that can perform these assessments economically and at full operational speed.
According to the Railway Tie Association, the U.S. rail network spans 140,000 miles of track supported by more than 450 million rail ties, with approximately 16 million ties replaced annually. By enabling continuous monitoring and classification of ties, Mobix Labs鈥� technology aims to reduce maintenance costs, extend tie lifecycles, and enhance rail safety for carriers across the country.
鈥淭his collaboration marks an important step in applying advanced sensing and AI to critical infrastructure,鈥� said Russell Cyr, Vice President and General Manager, Mobix Labs. 鈥淲e see significant potential to modernize rail maintenance practices, improve safety, and ultimately deliver a scalable solution for railroads worldwide.鈥�
About Mobix Labs
Based in Irvine, California, Mobix Labs is a fabless semiconductor company delivering advanced wireless and wired connectivity, RF, switching, and filtering technologies for next-generation communication systems. Our solutions support aerospace, defense, 5G, medical, industrial and other high-reliability markets. We specialize in electromagnetic interference (EMI) solutions for secure aerospace GPS systems, optical cables for high-speed interconnects and AI datacenters, mmWave radar and imaging for commercial applications, ensuring high performance and reliability in demanding applications. Visit , and follow us on .听
Forward-Looking Statements.
This press release contains 鈥渇orward-looking statements鈥� within the meaning of the federal securities laws, including Section 27A of the Securities Act of 1933 and Section 21E of the Securities Exchange Act of 1934. Forward-looking statements include, but are not limited to, statements regarding Mobix Labs, Inc.鈥檚 (鈥淢obix Labs鈥� or the 鈥淐ompany鈥�) current expectations, intentions, strategies, beliefs, or projections concerning future events or the Company鈥檚 future performance. These statements are often identified by words such as 鈥渁nticipate,鈥� 鈥渂elieve,鈥� 鈥渃ould,鈥� 鈥渆xpect,鈥� 鈥渋ntend,鈥� 鈥渕ay,鈥� 鈥減lan,鈥� 鈥減roject,鈥� 鈥渟eek,鈥� 鈥渟hould,鈥� 鈥渢arget,鈥� 鈥渨ill,鈥� 鈥渨ould,鈥� or similar expressions. These statements are subject to numerous risks and uncertainties that could materially affect Mobix Labs鈥� business, financial condition, and results of operations.
Forward-looking statements in this release include, but are not limited to, statements regarding the development, performance, scalability, commercialization, and future deployment of the Company鈥檚 AI-driven rail safety technologies; anticipated benefits to the rail industry from such technologies; expected timelines for development phases; and the Company's broader strategic goals related to innovation in infrastructure safety and data-driven monitoring solutions.
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Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of the date they are made. The Company undertakes no obligation to update or revise any forward-looking statements, whether as a result of new information, future events or otherwise, except as required by law.
Contacts
Media Contact:
Chris Lancaster, Mobix Labs, Inc.
Investor Contact:
Ryan Battaglia, Mobix Labs, Inc.
RF & MMW Product Contact:听
Russell Cyr, RaGE Systems
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