helping our furry companions live healthier, longer lives

The Tably API uses the power of artificial intelligence to help your user’s understand their cat’s subtle facial cues.

How Does the Tably API Work?

By accessing the Tably API, a photo of a cat says a thousand words - or maybe just a few - giving cats a voice to say whether they’re in pain or not.

Our highly accurate AI model assesses a photo against validated veterinary pain scales.

Our model has assessed hundreds of thousands of photos with over 85% precision. It utilizes proprietary machine learning algorithms to empower cat parents and veterinarians to make informed decisions about cat’s health & wellbeing.

Tably employs a number of artificial intelligence processes: object detection, image suitability detection, object extraction, image categorization and result analysis. To minimize errors, we have configured our algorithm to validate the presence of a feline face in the image before sending it to the AI model for further analysis.

Validated Veterinary Pain Scales

The Tably pain scale leverages traditional veterinary feline pain assessment protocols. These protocols have been proven to help determine how much pain a cat is feeling and typically take into account five facial cues: ear position, orbital tightening, muzzle tension, whisker positions and head position.

Our powerful AI model interprets cat wellbeing for veterinarians and cat parents alike. Furthermore, monitoring can happen in the clinic or remotely at home. Results are easily shard to ensure vets and cat parents are reviewing the same insights.

The Tably API works in a variety of situations

Ideal Photos

  • Well-lit

  • Uncluttered background

  • Cat is facing the camera directly

  • Photo is taken at direct angle

 

Not Ideal Photos

  • Blurry or poorly lit

  • Cat is not looking at the camera or face is not fully in the frame

  • Photo is taken at an upwards or downwards angle

 

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Definitions

  • Artificial Intelligence (AI) is computer intellect that can perceive, make decisions, and solve problems. AI helps with augmentation and automation of tedious or repetitive tasks.

  • Machine learning, a subset of artificial intelligence, enables computers to learn without being explicitly programmed. By looking at a large number of labelled images, machine learning algorithms can find small patterns across an array of pictures and use these patterns to assess new photos. As a dataset grows larger, the artificial intelligence model grows smarter. This allows inaccuracies to be minimized and deeper insights to be brought forward.

  • Computer Vision is a type of machine learning that gives machines a high-level understanding of video and/or still images by automating the tasks of human vision, allowing computers to understand and interpret the visual world. Tasks include object detection, object recognition, object tracking, 3D scene construction and more.