Beamr to Present its ML-Safe Video Data Stack to AV Engineers at AutoSens USA

Beamr (NASDAQ:BMR) will present its ML-safe video data stack for autonomous vehicles at AutoSens USA 2026, held June 9–11 in Detroit.

Rhea-AI Summary

Beamr (NASDAQ:BMR) will present its ML-safe video data stack for autonomous vehicles at AutoSens USA 2026, held June 9–11 in Detroit.

The stack targets petabyte-scale AV training pipelines, offering up to 50% video file size reduction while maintaining model performance, based on validated studies.

Argus May 20 session

+0.55% close to close Open Argus

Details

News Market Reaction – BMR

On May 20, the day this news came out, BMR closed 0.55% above the previous close.

Data tracked by StockTitan Argus for the May 20 session.

Key Figures

Conference dates: June 9–11, 2026 Booth number: 315 File size reduction: up to 50% +2 more

Conference dates

June 9–11, 2026

AutoSens USA 2026 in Detroit

Booth number

315

Beamr booth at AutoSens USA 2026

File size reduction

up to 50%

ML-safe video data stack compression claim

Depth error reduction (VRUs)

30.7%

Depth model trained on Beamr-compressed footage

Training data compression

35.2%

Depth model training data vs baseline

Historical Context

5 past events · Latest: May 12

5 events

1. May 12

   Conference AV demo

   24h Move

   -3.7%

   Planned Smart Mobility Summit demo of ML-safe AV video data stack.

2. May 06

   AI research update

   24h Move

   -1.0%

   Research validating CABR compression as an AI training asset.

3. Apr 20

   Partner validation

   24h Move

   +4.4%

   dSPACE RTMaps validation of ML-safe compression for AV data.

4. Apr 10

   Product launch

   24h Move

   +6.9%

   Launch of VISTA platform for large-scale subjective video testing.

5. Mar 12

   Conference demo

   24h Move

   +1.8%

   GTC 2026 demo of ML-safe compression for physical AI workflows.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Key Terms

ml-safe, autonomous vehicles (av), adas, content-adaptive bitrate (cabr), +2 more

6 terms

ml-safe technical

"Beamr is offering its ML-safe video data stack, enabling up to 50% file size..."

ml-safe means data, content or a process is suitable for use with machine learning systems because it avoids privacy risks, sensitive information, and formats that would break model training. Investors should care because ml-safe materials can be used to build or validate AI tools without legal or ethical roadblocks—like giving a chef pre-washed, pre-cut ingredients that are ready to cook rather than raw, uncertain supplies that could cause delays or liability.

autonomous vehicles (av) technical

"its ML-safe video data stack for autonomous vehicles (AV) at AutoSens USA 2026..."

Autonomous vehicles (AV) are cars, trucks, or other road vehicles equipped with sensors and software that let them navigate and operate without a human driver, like a vehicle with an onboard autopilot or self-driving taxi. For investors, AVs matter because they can change costs and revenue across industries—reducing labor and accident expenses, creating new service models, and reshaping supply chains and regulation—so developments affect company valuations and long-term growth prospects.

adas technical

"AutoSens is an AV and ADAS engineering-focused conference, attracting professionals..."

Advanced Driver Assistance Systems (ADAS) are electronic systems in vehicles that assist the driver with safety tasks. Examples include automatic emergency braking, lane keeping assist, and adaptive cruise control. These systems use sensors and cameras to improve vehicle safety.

content-adaptive bitrate (cabr) technical

"video compressed with its patented content-adaptive bitrate (CABR) technology..."

Content-adaptive bitrate (CABR) is a video-delivery method that adjusts streaming quality in real time based on both the viewer’s network conditions and the complexity of what's on-screen, so simple scenes use less data while complex scenes get more detail. For investors, CABR matters because it can improve user experience and reduce bandwidth costs, which affects subscriber retention, platform scalability, and the economics of streaming services.

vulnerable road users (vrus) technical

"depth model... on vulnerable road users (VRUs), including pedestrians and motorcyclists..."

Vulnerable road users (VRUs) are people who travel on roads with little or no physical protection—such as pedestrians, cyclists, motorcyclists, scooter riders and sometimes non-motorized road users. Investors care because changes in safety rules, vehicle technology, infrastructure spending and liability risk that aim to protect these groups can shift costs, demand and regulation for automakers, insurers, city planners and mobility service companies, much like weather changes how farmers budget and insure crops.

physical ai technical

"As autonomous driving advances and integrates with Physical AI applications..."

Physical AI combines artificial intelligence with physical devices or environments, enabling machines to interact with and adapt to the real world in a human-like way. It matters to investors because it can lead to smarter robots, autonomous vehicles, or advanced sensors that improve efficiency and open new markets, potentially creating significant business opportunities and competitive advantages.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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Herzliya, Israel, May 20, 2026 (GLOBE NEWSWIRE) -- Beamr Imaging Ltd. (NASDAQ: BMR), a leader in video optimization technology and solutions, today announced that it will present its ML-safe video data stack for autonomous vehicles (AV) at AutoSens USA 2026, held from June 9–11 in Detroit. AutoSens is an AV and ADAS engineering-focused conference, attracting professionals and leaders from OEMs, Tier 1, and supply chain companies.

To schedule a meeting with Beamr's team (booth 315), use this link.

As autonomous driving advances and integrates with Physical AI applications, the training and validation pipelines performance determine how far the model development can advance. Perception, validation, and simulation engineers need a proven compression approach that will support these scalable pipelines, often reaching hundreds of petabytes.

Beamr is offering its ML-safe video data stack, enabling up to 50% file size reduction without degrading model performance. The stack was validated from perception models through to world foundation models, on real-world and synthetic footage.

Recently, Beamr demonstrated that video compressed with its patented content-adaptive bitrate (CABR) technology can be used as an augmentation step in AI model training. The study demonstrated that treating compression as a training strategy allows it to scale efficiently while preserving the perception accuracy ML systems depend on. A state-of-the-art depth model trained with Beamr-compressed footage, delivered a 30.7% reduction in depth error on vulnerable road users (VRUs), including pedestrians and motorcyclists, while compressing the training data by 35.2% compared to baseline.

"AV engineers managing the petabyte-scale video data pipelines need to train, validate, and scale their systems with confidence. The conversation about video compression has moved from storage and infrastructure decisions into the training pipeline itself," said Beamr CEO, Sharon Carmel. “At AutoSens, we're showing that ML-safe compression can become a foundational layer for the perception models AV programs are building and the Physical AI systems they are integrating with."

To test Beamr's technology on your own data, schedule a meeting at AutoSens USA (booth 315) here.

About Beamr

Beamr (Nasdaq: BMR) is a world leader in content-adaptive video compression, trusted by top media companies including Netflix and Paramount. Beamr’s perceptual optimization technology (CABR) is backed by 53 patents and a winner of Emmy® Award for Technology and Engineering. The innovative technology reduces video file sizes by up to 50% while preserving quality and enabling AI-powered enhancements.

Beamr powers efficient video workflows across high-growth markets, such as media and entertainment, user-generated content, machine learning, and autonomous vehicles. Its flexible deployment options include on-premises, private or public cloud, with convenient availability for Amazon Web Services (AWS) and Oracle Cloud Infrastructure (OCI) customers.

For more details, please visit www.beamr.com or the investors’ website www.investors.beamr.com

Forward-Looking Statements

This press release contains “forward-looking statements” that are subject to substantial risks and uncertainties. Forward-looking statements in this communication may include, among other things, statements about Beamr’s strategic and business plans, technology, relationships, objectives and expectations for its business, the impact of trends on and interest in its business, intellectual property or product and its future results, operations and financial performance and condition. All statements, other than statements of historical fact, contained in this press release are forward-looking statements. Forward-looking statements contained in this press release may be identified by the use of words such as “anticipate,” “believe,” “contemplate,” “could,” “estimate,” “expect,” “intend,” “seek,” “may,” “might,” “plan,” “potential,” “predict,” “project,” “target,” “aim,” “should,” “will” “would,” or the negative of these words or other similar expressions, although not all forward-looking statements contain these words. Forward-looking statements are based on the Company’s current expectations and are subject to inherent uncertainties, risks and assumptions that are difficult to predict. Further, certain forward-looking statements are based on assumptions as to future events that may not prove to be accurate. 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 filed with the SEC on February 26, 2026 and in subsequent filings with the SEC. Forward-looking statements contained in this announcement are made as of the date hereof and the Company undertakes no duty to update such information except as required under applicable law.

Investor Contact:
investorrelations@beamr.com

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What will Beamr (NASDAQ:BMR) present at AutoSens USA 2026?

Beamr will present its ML-safe video data stack for autonomous vehicles, focused on compression for AI training pipelines. According to Beamr, this stack enables up to 50% video file size reduction while preserving AV perception and validation model performance at petabyte scale.

When and where is AutoSens USA 2026 where Beamr (BMR) is presenting?

AutoSens USA 2026 takes place June 9–11 in Detroit, bringing together AV and ADAS engineers. Beamr plans to showcase its ML-safe video data stack there, targeting OEMs, Tier 1, and supply chain professionals managing large-scale AV video training pipelines.

How does Beamr’s ML-safe video data stack benefit AV model training for BMR stakeholders?

Beamr’s stack is designed to compress AV training data by up to 50% without degrading model performance. According to Beamr, it supports scalable perception, validation, and simulation pipelines that can reach hundreds of petabytes, helping engineers manage storage and training efficiency.

What AI training results has Beamr (BMR) reported using its CABR video compression?

Beamr reports that its CABR-compressed video, used as a training augmentation, cut depth error by 30.7% on vulnerable road users. According to Beamr, this came while compressing training data by 35.2% versus baseline for a state-of-the-art depth perception model.

How can AV engineers meet Beamr at AutoSens USA 2026?

AV engineers can meet Beamr at booth 315 during AutoSens USA 2026 in Detroit. According to Beamr, visitors can schedule meetings to test the ML-safe video data stack on their own AV datasets and discuss integrating compression into training pipelines.

Why is Beamr’s video compression relevant for autonomous vehicle and Physical AI systems?

Beamr positions compression as part of the AV training pipeline, not just storage. According to Beamr, ML-safe compression can act as a foundational layer for perception models and emerging Physical AI systems that depend on massive, high-quality video datasets for training and validation.