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The smartest visual recognition system in the world

Our LLM-based AI understands behavior, events, and intent

Our AI monitors camera feeds in real time

And responds by communicating with other devices. No new hardware needed.

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Action & intent awareness

Woman_grocery_annotated.png

MATERIAL MODEL

The woman is: 

  1. Standing in the produce section, near a refrigerated display of fruits (apples, strawberries, and other berries are visible).

  2. Holding and examining a clear plastic container of dark berries (likely blueberries or blackberries).

  3. Carrying a large, light-colored reusable tote bag, into which she might be about to place the berries.

image.webp

State-of-the-art traditional computer vision March 10, 2025

YOLOE-11L

1 person 0.90 confidence

1 shopping bag 0.66 confidence

1 cup 0.52 confidence

1 canvas 0.48 confidence

1 shelf 0.48 confidence

1 gift basket 0.41 confidence

1 podium 0.39 confidence

Nuance sensitivity

Moving_boxes_annotated.png

MATERIAL MODEL

  1. There are a total of 9 boxes visible in the image: 3 stacked on the ground to the left, 1 being held by the man, 2 inside the van, 3 next to the hand truck on the right.

  2. There are 4 boxes with a visible "FRAGILE" label: The top box in the stack on the left, the tall box on the hand truck, the top box in the stack on the right, and the bottom held by the man.

  3. The top box in the stack on the left is open, since it has its flaps up.

storage-box-yolo.webp

State-of-the-art traditional computer vision March 10, 2025

YOLOE-11L

7 storage boxes 0.34-0.86 confidence

Context-dependent reasoning

Kid_cupcake.png

MATERIAL MODEL

  1. The child is messily eating a cupcake or a piece of cake.

  2. They have white frosting smeared around their mouth and on their hands while holding the treat.

kid-messy-yolo.webp

State-of-the-art traditional computer vision March 10, 2025

YOLOE-11L

1 child 0.75 confidence

1 snack 0.65 confidence

1 bite 0.60 confidence

1 donut 0.50 confidence

1 swab 0.37 confidence

One platform. Endless use cases.

Just describe what to look out for and what to do

  • Procedure supervision

    OSHA compliance

    Machinery monitoring

    Inventory tracking

    Quality control

    Protocol adherence

    Action logging

  • Theft prevention

    Internal shrink monitoring

    Activate warning alarms

    Speak to offender

    Entry and exit tracking

    Facial recognition

    Save/send footage of offense

    Alert guard

    Auto-locking doors

    Detecting suspicious activity

  • Theft prevention

    Intent inference

    Behavior analysis

    Inventory tracking

    Misplaced item recognition

    Facial recognition

    Alerting employees

    Safety monitoring

  • Safety monitoring

    Employee supervision

    Entry and exit tracking

    Behavior analysis

    ADL logging

    Reminders for forgotten actions

    Rule adherence tracking  

  • Procedure supervision

    Safety monitoring

    Entry and exit tracking

    Inventory tracking

    Shrink prevention

    Facial recognition

  • Health monitoring

    Behavior supervision

    Entry and exit tracking

    Security

  • Rule-following reminders

    Behavior monitoring

    Entry and exit tracking

    Safety supervision

The tech you've seen in sci-fi
is here for you to try.

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