As pet healthcare increasingly shifts toward early detection and preventive care, continuous health monitoring is emerging as a valuable tool for identifying potential concerns before visible symptoms appear. PetPace is advancing this approach with an AI-powered health-monitoring collar that tracks vital signs, activity, sleep, and other physiological indicators to identify meaningful deviations from an individual pet’s baseline. Through its availability on Chewy, the company aims to expand access to proactive pet health monitoring while connecting pet parents with veterinary support. In an exclusive conversation with AI Reporter America, Daniel Galitzky, Head of Software and Hardware Development at PetPace, discussed how AI-driven wearables are advancing pet health monitoring, the challenges of ensuring reliable clinical insights, and the potential of continuous data to transform preventive veterinary care.

1. What drove PetPace to advance AI-powered pet health monitoring through Chewy?

It's about reach and context. Chewy is where pet parents already go for everything their pets need. Chewy is also building out the healthcare side: it agreed to acquire Modern Animal, a veterinary platform with 29 owned clinics, 24/7 virtual care, and a membership model. A health-monitoring collar fits naturally into that ecosystem. As our CEO Gil Shetrit put it, the launch brings our technology to millions of pet parents who already turn to Chewy, and moves us closer to making proactive pet healthcare accessible to every pet parent.

2. How does PetPace use AI to track pets' vital signs and detect potential health changes?

The collar uses multiple non-irradiating, non-invasive, passive sensors. It monitors vital signs including pulse, respiration, temperature, and heart rate variability, along with activity, sleep, calories, posture, and other health indicators. The AI's job is to learn each animal's normal baseline. It then flags deviations that matter, such as a sustained rise in resting pulse, abnormal respiration, or changes in HRV that point to stress or pain. A single reading in isolation tells you very little; the baseline is what gives it meaning.

3. What sets its AI-powered monitoring technology apart from conventional pet wearables?

Most pet wearables are activity trackers with GPS. Unlike traditional activity-focused pet wearables, PetPace is designed specifically for health monitoring. In practice, this gives us capabilities that step counting can't provide:

• AI-driven, clinically validated pain scoring.
• Monitoring of epilepsy episodes and recording of seizure events.
• Integrated veterinary access, so the data doesn't just sit in an app.

4. How can continuous health insights help pet owners identify concerns earlier?

Pets instinctively hide pain and illness. By the time an owner notices symptoms, the problem is often advanced. Continuous monitoring captures the physiological signals that come before visible symptoms, such as subtle trends in temperature, respiration or HRV. Spot checks at an annual vet visit miss these. Continuity is the key: a trend over days is far more informative than one measurement taken in a stressful clinic environment.

5. How does PetPace translate complex health data into actionable insights for pet parents?

Pet parents don't need raw waveforms. They need to know whether something is wrong and what to do about it. The app turns sensor data into alerts, wellness scores and trends, and Apple Watch compatibility gives pet parents access to important health information directly from their wrist. The most important step is the handoff to a professional: the subscription includes 24/7 chat and video access to veterinarians contracted by PetPace in the app, and the vet sees the same data the owner does.

6. What challenges remain in ensuring accurate, reliable AI-driven pet health monitoring?

There are several real ones:

• Signal quality. Measuring vitals through fur, on an animal that runs, scratches and rolls, is much harder than on a human wrist. Motion artifacts and sensor contact remain ongoing engineering problems.
• Population diversity. A Chihuahua and a Great Dane, or a dog and a cat, have very different physiology. Models must generalize across breeds, sizes, and ages without being tuned to an "average pet" that doesn't exist.
• Ground truth. Pets can't report symptoms, so labeled clinical data is scarce and expensive to collect. That's why validation with vets and research institutions matters so much.
• Alert balance. Too many false alarms and owners stop paying attention; too few and you miss real problems. Calibrating this is a continuous process.
• Positioning. A collar supports veterinary judgment; it doesn't replace diagnosis. We have to be clear about that.

7. How could AI-powered wearables shape the future of preventive veterinary care?

Wearables can shift veterinary care from reactive to preventive. Instead of a once-a-year snapshot, vets get a continuous health history. This makes earlier interventions, better management of chronic conditions, and more objective follow-up after treatment or surgery possible. At scale, aggregated data can also advance veterinary research by revealing patterns across breeds and conditions that are invisible in individual clinic visits. The end goal is simple: catch problems while they're still small, cheaper, and more treatable.