Can AI reduce charting burden and support better client communication?

AI is emerging as a practical tool for busy veterinary teams, especially as documentation demands continue to grow. At the same time, the term itself has become a buzzword attached to almost every marketing gimmick. How can clinicians separate fact from fiction and determine what really works? In a recent dvm360 interview, CoVet co-founders Yannick Bloem, CEO, and Mike Mossop, DVM, CVO, discuss real-world applications of AI documentation for veterinary teams. Their insights focus on tangible gains like faster, more accurate medical records, smoother handoffs, and more time for patient care.

Editor’s note: This dvm360&A has been lightly edited and consolidated from a verbal interview to better fit a written format while retaining the substance of the original conversation.

dvm360: What is CoVet and what problem were you trying to solve?

Mossop: CoVet is an AI co-pilot, a digital assistant built specifically for veterinarians rather than for the practice as a whole. Our foundation is documentation: turning exam-room recordings into structured medical records with speech-to-text. But we’re building much more—reminders, interactions with practice management systems (PIMS), and clinical support tools—all designed to make the vet’s job easier and more efficient.

dvm360: How can AI save time and reduce burnout in practical terms?

Bloem: Vets spend hours on documentation. In many clinics that’s a few extra hours every night. CoVet can cut that down to minutes. Practically, that means clinicians get home on time, see 1 or 2 additional patients per day in some cases, and deliver better quality documentation. The downstream effects are lower burnout, lower turnover, and a better client experience because the clinician can give full attention to the client during the visit.

dvm360: You mentioned bedside manner. How does AI actually improve client interactions?

Yannick: When note-taking is automated, vets don’t have to split attention between typing and talking. That yields fuller, more focused conversations and clients leave with clear visit summaries. Fewer callbacks for clarification means happier clients and less follow-up work for staff.

dvm360: Accuracy and hallucination are big concerns. How do you manage those risks?

Mossop: There are 2 use cases to separate. For clinical reference content, we source information from vetted veterinary data providers and present citations so clinicians can verify the source. For documentation, like turning a consult into a record, the clinician remains the final arbiter. We have an in-house medical team that reviews outputs and a board of consulting specialists to refine the system for specialties. Importantly, our telemetry shows that on average 95% of the generated record is left untouched though clinicians always validate before finalizing. We also learn from user feedback and continually improve the models.

dvm360: Is CoVet flexible for multi-doctor clinics and for non-veterinarian staff?

Mossop / Yannick: Yes. Practices can standardize templates across the team or allow individual customization. That flexibility is valuable for locums or vets who work in multiple clinics the system follows the clinician. And it’s not only for vets: technicians, CSRs, and clinic managers use CoVet for history-taking, call summaries, meeting notes, billing handoffs, and more. When a vet subscribes, the entire team can be involved through free support accounts.

dvm360: How much does integration with PIMS matter?

Yannick: Integrations are important, and we’re building real API integrations with many systems. We also provide a Chrome extension for cloud-based PIMS that speeds workflows even without a full integration. But the majority of users derive large efficiency gains without full integration the core value (the 95% of gains) is available even before the last few percent of automation provided by a direct API.

dvm360: What should clinics ask vendors during demos?

Mossop: Ask who owns and controls the data, and how it’s stored and used. Ask what percent of generated notes are edited and what counts as an “edit.” Confirm whether clinical recommendations include citations and how hallucinations are managed. Ask which PIMS are supported and whether features are available to non-doctor staff. Finally, check security and compliance—encryption at rest/in transit—and get those guarantees in writing.

dvm360: Any common misconceptions about AI you want to clear up?

Yannick / Mossop: You don’t need a full clinic overhaul to start using AI. Small steps work. Also, data-usage fears are valid. However, some vendors (including us) explicitly state that user data is owned by the practice and not used to train external models without consent. Lastly, a tool that’s only “80%” right won’t stick. Clinicians need the system to be 90–95% correct in tone, structure, and content for daily adoption.