Rail Vision (RVSN) unit integrates Google dataset into quantum decoder
Rhea-AI Filing Summary
Rail Vision Ltd., an early commercialization stage railway safety technology company, reports that its majority-owned subsidiary Quantum Transportation has integrated a publicly accessible experimental surface-code dataset from Google Quantum AI into its Quantum Error Correction (QECC) transformer pipeline. The team built a standardized data adapter for dense binary syndrome measurements, added dynamic attention masking tailored to code distances and layouts, and created an end-to-end training loop that handles mixed batches of real experimental shots. This milestone is presented as reducing technical risk by moving beyond internal data formats and enabling scalable training and benchmarking on an external testbed. Rail Vision holds a 51% stake in Quantum Transportation, which is developing transformer-based neural decoder technology for advanced quantum error correction, including cloud deployments on AWS with potential applications in transportation and other industries.
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Key Figures
Key Terms
Quantum Error Correction (QECC) technical
surface-code dataset technical
transformer-based neural decoder technical
forward-looking statements regulatory
Form 6-K regulatory
UNITED STATES
SECURITIES AND EXCHANGE COMMISSION
Washington, D.C. 20549
Form 6-K
Report of Foreign Private Issuer
Pursuant to Rule 13a-16 or 15d-16
under the Securities Exchange Act of 1934
For the month of May 2026
Commission file number: 001-41334
RAIL VISION LTD.
(Translation of registrant’s name into English)
15 Ha’Tidhar St
Ra’anana, 4366517 Israel
(Address of principal executive offices)
Indicate by check mark whether the registrant files or will file annual reports under cover of Form 20-F or Form 40-F.
| Form 20-F ☒ | Form 40-F ☐ |
CONTENTS
Attached hereto and incorporated herein is the Registrant’s press release issued on May 20, 2026, titled “Rail Vision: Quantum Transportation Successfully Integrates Google’s Public Surface-Code Dataset into its Quantum Error Correction Transformer.”
The first five paragraphs in the press release attached as Exhibit 99.1 are incorporated by reference into the Registrant’s Registration Statements on Form F-3 (File Nos. 333-271068, 333-272933, 333-277963 and 333-278645) and Form S-8 (File Nos. 333-265968, 333-281329 and 333-286652), filed with the Securities and Exchange Commission, to be a part thereof from the date on which this report is submitted, to the extent not superseded by documents or reports subsequently filed or furnished.
EXHIBIT INDEX
| Exhibit No. | ||
| 99.1 | Press release issued by Rail Vision Ltd. on May 20, 2026, titled “Rail Vision: Quantum Transportation Successfully Integrates Google’s Public Surface-Code Dataset into its Quantum Error Correction Transformer” |
SIGNATURES
Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.
| Rail Vision Ltd. | ||
| Date: May 20, 2026 | By: | /s/ Ofer Naveh |
| Name: | Ofer Naveh | |
| Title: | Chief Financial Officer | |
Exhibit 99.1
Rail Vision: Quantum Transportation Successfully Integrates Google’s Public Surface-Code Dataset into its Quantum Error Correction Transformer
Ra’anana, Israel, May 20, 2026 (GLOBE NEWSWIRE) – Rail Vision Ltd. (Nasdaq: RVSN, FSE: C80) (“Rail Vision” or the “Company”), an early commercialization stage technology company transforming railway safety through advanced AI-integrated sensing systems, announces today, that its majority owned subsidiary Quantum Transportation Ltd. (“Quantum Transportation”), a quantum computing innovator, has successfully delivered a working integration layer that brings a publicly accessible experimental surface-code dataset from Google Quantum AI, into the Quantum Transportation’s Quantum Error Correction (QECC) IP (patent pending) transformer pipeline.
In this phase, the team implemented a standardized data adapter to ingest dense binary syndrome measurements from selected experimental configurations, engineered dynamic attention masking that adapts to code distances and layouts, and established an end-to-end training loop capable of processing mixed batches of real experimental shots.
This milestone reduces technical risk by advancing QECC beyond controlled internal data formats and lays the foundation required for scalable training and repeatable benchmarking on a credible external testbed.
Quantum Transportation is developing transformer-based quantum decoder technology for advanced quantum error correction, including cloud-deployed neural decoders. The decoder’s IP (patent pending) is licensed from Ramot at Tel Aviv University, with applications in various potential industries and end users.
Quantum Transportation previously announced it has successfully implemented its transformer-based neural decoder on the AWS cloud, marking a significant milestone toward real-world quantum applications within the transportation sector. Building on the recent unveiling of its transformer neural decoder, which outperformed classical quantum error correction (QEC) algorithms in simulations, and the delivery of its first prototype for universal error correction, Quantum Transportation’s cloud deployment now provides the scalable infrastructure needed to process complex quantum data efficiently.
About Rail Vision Ltd.
Rail Vision (Nasdaq: RVSN) is an early commercialization stage technology company transforming railway safety through advanced AI-integrated sensing systems. The Company develops and commercializes proprietary, multi-spectral electro-optic platforms that provide extended-range situational awareness and real-time hazard detection. Using machine learning algorithms to identify and classify obstacles, Rail Vision’s technology enhances safety, improves operational efficiency, and supports continuity across deployments.
The Company’s cloud-based platform complements its products by transforming railway operational data into actionable insights that help optimize performance, reduce downtime, and improve safety. As the Company expands its global footprint, it delivers AI-driven perception that supports safer operations, reduces operational risk, and enables the transition to fully autonomous operations.
Rail Vision holds a 51% stake in Quantum Transportation, which has an exclusive sub-license for rail technologies under an innovative pending patent in quantum error correction owned by Ramot, the technology transfer company of Tel Aviv University.
For more information, please visit https://www.railvision.io/
Forward-Looking Statements
This press release contains “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act and other securities laws. Forward-looking statements contained in this press release include, but are not limited to, statements regarding Rail Vision’s and its subsidiary’s strategic and business plans, technology, relationships, objectives and expectations for its business, growth, the impact of trends on and interest in its business, intellectual property, products and its future results, operations and financial performance and condition and may be identified by the use of words such as “may,” “seek,” “will,” “consider,” “likely,” “assume,” “estimate,” “expect,” “anticipate,” “intend,” “believe,” “do not believe,” “aim,” “predict,” “plan,” “project,” “continue,” “potential,” “guidance,” “objective,” “outlook,” “trends,” “future,” “could,” “would,” “should,” “target,” “on track” or their negatives or variations, and similar terminology and words of similar import, generally involve future or forward-looking statements. Forward-looking statements are not historical facts, and are based upon management’s current expectations, beliefs and projections, many of which, by their nature, are inherently uncertain. Such expectations, beliefs and projections are expressed in good faith. However, there can be no assurance that management’s expectations, beliefs and projections will be achieved, and actual results may differ materially from what is expressed in or indicated by the forward-looking statements. Forward-looking statements are subject to risks and uncertainties that could cause actual performance or results to differ materially from those expressed in the forward-looking statements. For a more detailed description of the risks and uncertainties affecting the Company, reference is made to the Company’s reports filed from time to time with the Securities and Exchange Commission (“SEC”), including, but not limited to, the risks detailed in the Company’s annual report on Form 20-F, for the fiscal year ended December 31, 2025, filed with the SEC on March 31, 2026 and in subsequent filings with the SEC. Forward-looking statements speak only as of the date the statements are made. The Company assumes no obligation to update forward-looking statements to reflect actual results, subsequent events or circumstances, changes in assumptions or changes in other factors affecting forward-looking information except to the extent required by applicable securities laws. If the Company does update one or more forward-looking statements, no inference should be drawn that the Company will make additional updates with respect thereto or with respect to other forward-looking statements. 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. Rail Vision is not responsible for the contents of third-party websites.
Contacts
David
BenDavid
Chief Executive Officer
Rail Vision Ltd.
15 Ha’Tidhar St
Ra’anana, 4366517 Israel
Telephone: +972- 9-957-7706
Investor Relations:
Michal Efraty
investors@railvision.io