High volumes of violations
Camera‑based and LPR systems generate large volumes of potential violations that must be reviewed to ensure accuracy and prevent errors and inappropriate citation issuance.
Trellint equips cities with an automated enforcement review platform that validates camera-based violations before citations are issued. Every LPR capture and camera enforcement event passes through structured human and AI-assisted reviews, ensuring evidence is complete and accurate, and accountability is maintained throughout.
Growing volumes, disparate hardware providers and disconnected processes make it harder to ensure fair, confident and timely enforcement decisions.
Camera‑based and LPR systems generate large volumes of potential violations that must be reviewed to ensure accuracy and prevent errors and inappropriate citation issuance.
Reviewers rely on disconnected tools and manual processes, especially when multiple camera providers are deployed, slowing decisions, increasing inconsistency, and making quality control difficult.
Supervisors lack real‑time visibility into review queues, reviewer performance, and evidence quality, limiting their ability to intervene before issues escalate.
Trellint helps agencies reduce risk, improve consistency and accuracy, and maintain accountability across automated enforcement.
Camera‑based enforcement events, LPR captures, and supporting evidence come together in a single efficient review process that supports consistency and completeness as part of the citation issuance process.
Every potential violation is assessed for required evidence, context, and metadata before a citation proceeds. This citation evidence review system ensures decisions are accurate, consistent, and fully explainable when challenged.
Trellint provides review workflows that enable city teams to validate every LPR‑detected event before a citation is issued. Accuracy and accountability are embedded at the point of decision, not added retrospectively.
Supervisors monitor review queues, assess review quality, reallocate workloads, and escalate exceptions in real-time. The enforcement supervisor dashboard transforms oversight from retrospective audit into active quality control.
Red light, stop sign, bus lane, speed, and parking enforcement are reviewed through a single structured process, applying consistent standards that support quality and velocity as automated enforcement volumes increase.
Evidence, including images, video, certifications, and decision records, is securely stored and linked to each case. Customers can access this information online, improving transparency, supporting appeals, and reducing manual evidence handling.
Trellint’s platform connects review, decision-making, and case management into one continuous workflow, ensuring every automated enforcement decision is accurate, consistent, and fully accountable.
Kurbis Verify supports the structured review of camera-based events, bringing together imagery, video, and enforcement data in one place. Reviewers can validate evidence, ensuring that every decision is supported by complete and defensible information.
Comply connects enforcement activity across the wider program. It ensures that decisions made during automated review align with operational policy, and supports consistent enforcement across both on-street and camera-based activity.
An automated enforcement review system supports the structured review and validation of camera‑based traffic enforcement events. It ensures evidence is complete, decisions are consistent, and citations are issued only after appropriate human review.
Automated enforcement review platforms are used by parking, transit and traffic enforcement agencies, third-party enforcement providers, and supervisors responsible for LPR citation issuance, quality control, and operational oversight.
Trellint supports a wide range of camera-based traffic enforcement programs, including unpaid metered parking, red light violations, speed infractions, stop sign violations, school bus stop arm violations, and bus lane enforcement.
Yes. Our solutions are designed to integrate with existing enforcement, citation processing, and back-office systems, supporting multi-vendor environments and scalable automated enforcement operations.
Want to understand how automated traffic enforcement review can improve evidence quality, oversight, and consistency across your camera‑based enforcement programs?
Get in touch to explore how automated traffic enforcement review can strengthen evidence quality, oversight, and operational performance.