Plumerai's Video Intelligence pipeline is a complete AI solution for cameras and video doorbells, combining efficient on-device AI with a cloud-based Vision Language Model. It delivers AI Video Search, AI Captions, Multicam Re-identification, Familiar Face Identification, and People, Vehicle, Animal & Package Detection. Already deployed on millions of devices, it's the most accurate and compute-efficient solution on the market.
Every event is automatically described in clear, natural language. AI Captions combine efficient on-device Tiny AI with an optimized Vision Language Model in the cloud, turning raw footage into concise, readable summaries of what happened. They make notifications more informative and let users grasp activity at a glance without watching the full clip.
Find any moment in your video history using plain language. Powered by Plumerai's Video Intelligence pipeline, AI Video Search lets users describe what they're looking for, such as a person in a red jacket, a delivery, or a specific pet, and instantly surfaces the matching clips, with no endless scrubbing required.
Identifies individuals based on their clothing and physique, allowing seamless re-identification across multiple video clips from a single or multiple cameras. Merges and stitches video clips and notifications, reducing clutter and making it easy to review the entire activity.
Familiar Face Identification efficiently recognizes both household members and strangers, even from a distance. With automatic and manual face enrollment options, it delivers industry-leading accuracy, ensuring minimal missed or incorrect identifications. Compliant with local privacy laws, including GDPR, CCPA and BIPA.
Detects, localizes, and tracks people, vehicles, animals, and packages with precision, enabling real-time alerts and smart insights to the user. Customizable detection zones allow you to focus on specific areas, reducing false alarms and enhancing monitoring efficiency. Accurate detections ensure precise alerts in real-world conditions.
Filters out motion from rain, snow, dust, moving trees or plants, or lighting changes, focusing only on relevant motion. This greatly reduces false positives, ensuring notifications and recordings are triggered only by meaningful activity, thereby extending battery life and improving overall device efficiency.
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