Targage is an intelligence layer for parking garages and private lots. It analyzes DVR/NVR footage, detects plates, extracts text, and creates a precise timeline so operators can retrieve entry and exit moments in seconds.
Instead of forcing operators to replace their full camera setup, Targage acts as the intelligence layer above existing video systems: turning passive recordings into searchable evidence, operational history, and legal protection.
Positioning
Brain for existing cameras
Targage upgrades DVR and NVR footage with AI plate detection, OCR, and searchable timeline references without replacing the installed surveillance stack.
Security without lock-in
Deployable as a secure software layer on local infrastructure or controlled environments, with clear data access boundaries and auditable retrieval.
Operational outcome
From chaos to instant retrieval
Hours of manual review become seconds of plate lookup, with clip references ready for operators, managers, and dispute handling.
Targage is built around a real pain point: people losing hours scrolling recordings to answer simple vehicle-movement questions. The product compresses that work into fast search.
When surveillance exists, operators can be expected to reconstruct what happened. Targage helps turn footage into timestamped evidence instead of a liability trapped inside raw video archives.
The product is not another closed hardware ecosystem. It is a software intelligence layer designed to sit on top of existing installations and add value without forcing an overhaul.
Interactive simulation
This mock shows the user experience Targage aims for: search a plate, inspect the sightings timeline, and jump directly to the relevant clips instead of scrubbing through footage.
Total sightings
2
First seen
2026-03-24 08:11:27
Last seen
2026-03-24 18:42:09
Every result is designed to remain linked to original footage references, helping teams answer incidents with clear provenance and auditable access.
Indexed results
AB123CD
Timeline index
ANPR-Timeline
2026-03-24 08:11:27
White hatchback, front camera, clear daylight frame.
2026-03-24 18:42:09
Exit lane, rear capture cross-checked with timeline index.
Processes live streams and historical recordings directly from existing DVR/NVR storage and surveillance feeds, preserving the installed hardware as the visual input layer.
Locates license plates under real parking conditions such as glare, distance, and uneven lighting, then transcribes alphanumeric values through OCR and normalization logic.
Pairs each recognition event with timestamps, camera identity, and footage references in a structured searchable timeline that operators can query instantly.
Users search by plate number and retrieve the relevant entry, exit, and movement evidence immediately instead of manually reviewing long surveillance sessions.
Cuts video audit effort from hours of manual review to a few seconds per case.
Creates a reliable chronological logbook of every vehicle movement inside the facility.
Provides timestamped visual evidence to resolve damage disputes quickly and transparently.
Integration
The strongest strategic angle for Targage is hardware disintermediation: keep the cameras, upgrade the logic. That makes the product easier to adopt for operators, integrators, and parking facilities already invested in surveillance infrastructure.
Cybersecurity & GDPR
Targage represents a new standard in intelligent footage management. Not an aggressive surveillance tool, but a controlled and auditable technology layer designed to help organizations manage video evidence with maximum responsibility and full privacy awareness.
Deploy on local or controlled infrastructure when data sovereignty is a priority.
Support clear access rules, selective retrieval, and data-minimization-oriented workflows.
Help operators answer incidents with evidence faster, reducing unnecessary exposure to raw footage.
FAQ
Find answers to key technical and operational questions about Targage: from full regulatory alignment and system compatibility to concrete efficiency gains over manual video review.
No. Its main value is acting as a software intelligence layer over existing camera systems, DVRs, and NVRs, reducing the need for expensive hardware replacement.
It turns a time-heavy, error-prone review process into a plate-based search workflow, allowing staff to retrieve relevant entry and exit evidence in seconds instead of hours.
Because parking operators often need to reconstruct events during disputes. A searchable timeline with footage references is more defensible and more operationally useful than raw archives alone.
Parking operators, private garages, property managers, and system integrators who already have video infrastructure but need faster retrieval, better traceability, and a practical ANPR layer.
DevOP case study
A computer-vision layer that makes existing garage and parking video streams searchable by license plate.
DevOP role
Workflow analysis, detection and OCR pipeline, temporal index, operational search, and local-deployment architecture.
Avoid hours of manual footage review when an operator must reconstruct an entry, exit, or dispute.
The pattern is reusable for inspection, security, and event search in video archives without replacing field hardware.