COLUMBIA, Md., July 08, 2026 (GLOBE NEWSWIRE) -- Rekor Systems, Inc. (NASDAQ:REKR) ("Rekor" or the "Company"), a technology company developing trusted-data, privacy, security, and intelligence solutions for real-world transportation, public-safety, video, and sensor networks, today published a new white paper outlining Rekor's Privacy and Evidence Architecture for Responsible Vehicle Recognition.

The white paper is available here: ALPR AND PRIVACY: A practical framework for preserving public-safety value while reducing unnecessary privacy risk

As capabilities have expanded over the last decade, automated license plate recognition ("ALPR") and vehicle recognition technologies have become increasingly important tools for public safety. They can help agencies locate stolen vehicles, support Amber and Silver Alerts, identify wanted vehicles, protect critical infrastructure, and provide critical assistance for time-sensitive investigations.

At the same time, a growing national backlash against ALPR has become impossible to ignore. Public reporting, litigation, advocacy campaigns, and online discussion, much of it involving Flock Safety, have turned ALPR into a broader debate about the surveillance state, data sharing, retention, auditability, accuracy, and public trust.

Rekor believes the future of vehicle recognition should not be framed as an all-or-nothing fight. The better question is whether a model can be developed that preserves legitimate public-safety uses while protecting the privacy of ordinary citizens.

"ALPR has proved its value over many years of responsible use," said Robert A. Berman, Chair and Chief Executive Officer of Rekor Systems. "It's an indispensable tool for public safety. But legitimate issues are being raised around privacy, proper mechanisms for both data retention and sharing, auditability, and evidentiary trust. At Rekor, we believe these issues can be addressed thoughtfully and directly through better architecture."

Rekor's white paper outlines a three-part framework designed to help align public-safety and civil-liberties concerns more closely:

1. Protect non-relevant data by default

Information concerning a vehicle that isn't on a hotlist, wanted list, Amber or Silver Alert list, or other legally authorized investigative list does not have to be treated the same way as information that is relevant to a public-safety event. Rekor believes responsible vehicle recognition systems should protect the privacy of ordinary drivers by default while preserving authorized public-safety uses and has designed its systems accordingly.

2. Retain identifiable records based on purpose and policy

Traditional ALPR policies often rely on fixed information retention periods that may not distinguish between ordinary observations, authorized alerts, and records that must be retained for lawful purposes or investigative relevance. Rekor's products have been designed with the understanding that retention should be purpose-based, policy-driven, auditable, and tied to public-safety need, legal requirements, and community expectations.

3. Verify the integrity of video evidence when it matters

In a world where video can be edited, shortened, reposted, manipulated, generated by artificial intelligence, or challenged after the fact, Rekor believes responsible vehicle recognition should also address whether the underlying video evidence can be proven. Rekor's Go-Secure.Video technology is designed to authenticate video at the point of capture and support later validation when original media is produced.

"Privacy by design. Trust by proof. These should not be aspirations — they should be architectural decisions made before the first line of code is written. said Chris Kadoch, Chief Technology Officer of Rekor Systems. "Purpose-bound retention, verifiable evidence, this is what technical commitment looks like. Rekor has been building toward that standard for years."

The white paper proposes that a responsible framework for vehicle recognition should require systems to:

Protect non-relevant data by default, including through anonymization, encoding, or other privacy-protective treatment.
Preserve the ability to use authorized hotlists, and support wanted-vehicle, missing-person, and legally approved investigative uses.
Apply retention policies based on lawful purpose, offense severity, investigatory relevance, and rules that communities can support.
Maintain auditable access logs showing who accessed data, when, and for what purpose.
Verify the integrity of video evidence used to support alerts, investigations, claims, or litigation.
Support existing infrastructure and OEM ecosystems so agencies can modernize without unnecessary hardware replacement.

Rekor believes this framework provides a practical path forward for lawmakers, agencies, civil rights stakeholders, OEMs, and industry participants. Regulation does not need to eliminate vehicle recognition. It can require better outcomes: non-relevant data protection, purpose-based retention, auditable access, customer and community control, and evidence integrity.

The white paper discusses Rekor's technology and intellectual property in greater detail, including privacy protection, policy-based retention, and Go-Secure.Video in a responsible vehicle-recognition architecture.

"The market is changing," Berman added. "Customers still need advanced vehicle recognition, but they also need systems that can stand up to public scrutiny, regulatory review, and courtroom challenges. Rekor believes its privacy and evidence architecture provides a path for the industry to preserve the value of ALPR while addressing the legitimate public concerns around how the data is handled."

The white paper is intended as a discussion framework for policymakers, public safety leaders, civil rights stakeholders, technology partners, OEMs, and other industry participants to consider how vehicle recognition should operate in a more regulated environment.

About Rekor Systems, Inc.

Rekor Systems, Inc. (NASDAQ:REKR) is a technology company developing trusted data, privacy, security, and intelligence solutions for real-world transportation, public safety, video, and sensor networks. Rekor's advanced computer vision, machine learning, data security, and media authentication platforms help government agencies, public-safety organizations, transportation authorities, commercial customers, and technology partners transform visual, roadway, and sensor data into trusted, actionable intelligence. Rekor's solutions are designed to support safer, more efficient mobility, stronger public safety outcomes, privacy-conscious data practices, operational transparency, and evidentiary integrity.

To learn more, please visit https://rekor.ai and follow Rekor on LinkedIn, X, Threads, and Instagram.

Media & Investor Relations Contact

Charles Degliomini

Executive Vice President

Rekor Systems, Inc.

cdegliomini@rekor.ai

Forward-Looking Statements

Forward-Looking Statements

This press release and its links and attachments contains forward looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 concerning Rekor Systems, Inc. that involve substantial risks and uncertainties, including particularly statements regarding our future results of operations and financial position, business strategy, prospective products and services, timing and likelihood of success, plans and objectives of management for future operations and future results of current and anticipated products and services. These statements involve uncertainties, such as known and unknown risks, and are dependent on other important factors that may cause our actual results, performance, or achievements to be materially different from the future results, performance or achievements we express or imply. For this purpose, any statements that are not statements of historical fact may be deemed to be forward-looking statements. In some cases, you can identify forward-looking statements by terms such as "may," "will," "should," "expect," "plan," "anticipate," "could," "intend," "target," "project," "contemplates," "believes," "estimates," "predicts," "potential," or "continue," or the negative of these terms or other similar expressions. These forward-looking statements speak only as of the date they are made and are subject to a number of risks, uncertainties and assumptions described under the sections in our Annual Report on Form 10-K for the year ended December 31, 2025 entitled "Risk Factors" and in our subsequent Quarterly Reports on Form 10-Q filed with the SEC. Given these risks and uncertainties, readers are cautioned not to place undue reliance on such forward-looking statements. Readers are urged to carefully review and consider the various disclosures made in this Press Release and in other documents we file from time to time with the SEC that disclose risks and uncertainties that may affect our business. The forward-looking statements in this Press Release do not reflect the potential impact of any divestiture, merger, acquisition, or other business combination that had not been completed as of the date of this filing. Because forward-looking statements are inherently subject to risks and uncertainties, some of which cannot be predicted or quantified and some of which are beyond our control, you should not rely on these forward-looking statements as predictions of future events. These forward-looking statements are qualified in their entirety by reference to the risks discussed in our SEC filings. This cautionary statement also applies to any forward-looking statements made during the conference call referenced herein. We do not undertake any obligation to publicly update any forward-looking statements, whether as a result of the receipt of new information, the occurrence of future events, or otherwise.