The power of trusting us
Let your business be protected with Intelligent Video Analytics - The capability of automatically analyzing video stream from security cameras.
AiLert brings visual data and AI together to improve operational efficiency and safety. Using already installed security cameras you can now deploy, and scale SAMSON weapon detection at edge.
When every second counts
The Company continuously aligns its business model with GDPR, LED, EGTAI, ALTAI, and other legal and technical regulations and standards. The Company not only continuously endeavors to be fully compliant with the relevant EU law (primarily General Data Protection Regulation (GDPR) and Law Enforcement Directive (LED Directive)) but additionally makes its best efforts to ensure that its clients satisfy the same track record. The Company promotes using Standard Contractual Clauses, provided the clients are interested in such a contractual arrangement. The Company is fully devoted to democratic values and the protection of democratic processes and deliberations, and endeavors to align its operation with relevant technical standards (such as ISO and IEEE) and relevant ethical and legal recommendations (such as Ethics Guidelines for Trustworthy AI (EGTAI), and The Assessment List for Trustworthy AI (ALTAI)). Equally so, and whenever possible, the Company strives to extend the reach of fundamental EU values to a wide range of its clients, many of whom are established outside the EU. In effect, the Company plays a role in the global outreach of the GDPR as a mechanism aimed at protecting personal data on a global scale.
AiLert is:
An IT company delivering state-of- the-art artificial intelligence powered weapons detection tool (WDT tool) based on machine learning capacity.
A data processor who processes CCTV camera footage delivered by the clients.
A company operating from Israel that is considered as a third country safe for data transfers to and from the European Union (adequacy requirement).
AiLert will ensure:
Privacy by design and privacy by default mechanisms with the incorporated automatic pseudonymization of footage to be reviewed by human security operators.
That no personal data contained in the footage is incorporated into the algorithm, and that all third-party footage utilized for algorithm data training is permanently deleted after the retraining is finished.
Support to its clients and other relevant stakeholders (law enforcement bodies, data protection authorities, and others) in achievingthe standard of AI explainability by providing technical assistance and guidance regarding the WDT tool and its performance.
Continuous investment into AI development (technical accuracy), detailed data processing record-keeping system, and a traceability system enabling self- assessment and third-party assessment.
AiLert embraces the Ethics Guidelines for Trustworthy AI by relying on:
The data minimization principle – whereby access to personal data is enabled (on request or by default) only when the WDT tool issues an emergency alert and when the human security operator evaluates and validates or negates such finding (positive and negative detections).
The human-in-theloop principle – whereby the WDT tool is not coded to make decisions but recommendations that need to be evaluated and validated by human security operators.
The human agency principle – whereby the WDT tool does not allow any autonomous AI decision-making but is based on an AI recommendation output that is scrutinized by a human security operator.
The human-incommand principle – whereby no WDT tool’s generated alerts produce any effect without specific approval or denial issued by a human security.
The human oversight principle – whereby the WDT tool has an integrated access to all system records and enables a realtime and post hoc oversight of AI systems and their performance, including data analysis and alert recommendations.
The necessity principle – whereby the Company will utilize false positive detection footage only to the extent that it is necessary to use incorrect object categorizations to improve the algorithm’s detection and learning capacity.
The proportionality principle – whereby the Company will utilize false positive detection footage for algorithm retraining that incidentally contains personal data, where the access to the noted personal data is proportional to the overall use of the footage for data retraining.
Quality and enthusiasm to work
Quality is something we believe let us to improve.
For this reason our solutions will improve your projects.