Why fragmented pet tech data is falling short in modern pet care

Fragmented pet tech data is becoming a bigger problem as connected devices, AI tools, and veterinary records all generate useful information that often can’t be combined in a clinically meaningful way. A recent GlobalPETS report spotlights MOVA’s push to build an integrated ecosystem around smart devices and an AI-driven “digital twin” for pets, arguing that litter box, feeding, hydration, and activity data are more valuable when viewed together rather than as isolated signals. That industry vision overlaps with a broader veterinary conversation: in a recent AVMA Veterinary Vertex episode, researcher Lauren Grant described how companion animal surveillance still relies heavily on disconnected data streams and limited reporting, making it harder to integrate animal, human, and environmental information for timely risk detection. (barchart.com)

Why it matters: For veterinary professionals, the issue isn’t just gadget overload. It’s whether home-generated data can be standardized, shared, and interpreted in ways that improve care instead of adding noise. Existing surveillance and research efforts have shown the value of pulling records from practice management systems and diagnostic labs into larger datasets, while newer commentary on pet AI argues that continuous device data may help establish baselines and detect change earlier. But without interoperability, common terminology, and workable clinic workflows, much of that information stays trapped in silos outside the medical record. (pubmed.ncbi.nlm.nih.gov)

What to watch: Expect the next phase to center on whether pet tech companies can connect consumer data with veterinary systems in a way that supports surveillance, privacy, and real clinical decision-making, rather than just consumer engagement. (veterinaryvertex.buzzsprout.com)