ALPR and vehicle attribute extraction with a confidence-gated review queue. Your operators only see the plates the model isn't sure about — everything else auto-approves.
Upload an image or a batch of video frames. Neural Sentinel returns plate number, state, make/model/year, and color — each with a confidence score.
Trained on tolling imagery — angled plates, reflections, partial occlusion, mixed U.S. formats.
State inferred from plate artwork and layout. 51 U.S. jurisdictions supported, including specialty issues.
Trim-level identification when possible. Reviewers can override the model if needed.
Normalized color field for filtering and search — not affected by plate enhancement filters.
High-confidence detections auto-approve. Low-confidence detections land in a queue your team can burn through with the keyboard.
Each vehicle is scored on plate, state, and vehicle attributes. Anything above your threshold is auto-approved and exported. Anything below routes to the queue — usually 15–25% of traffic.
When the plate is dark, glared, or low-contrast, your reviewer doesn't need Photoshop — the enhancements panel is built in.
One-click presets — Auto, Hi-Contrast, Night, Deblur, Glare, Grayscale — cover the common cases. Fine-tune brightness, contrast, sharpness, saturation, exposure or gamma when a plate needs it. Enhancements apply only to the plate crop, so the vehicle shot stays true.
Every reviewed vehicle keeps the full record: the vehicle crop, the plate crop, extracted plate number and state with confidence, make/model/year, color, and detection metadata — frame index, timestamp, bounding box. Previous / Next moves you through the batch without a single mouse click.
The pipeline, the people tiers, and what you get as a buyer.
Pilot Neural Sentinel on a day's worth of your tolling imagery and measure how much of it auto-approves. Our team handles the integration.