Why don’t we offer the same to animals?At CompanAIn, we’re changing that.
If you’ve spent time inside human healthcare lately, you’ve probably heard the term: Agentic AI. Agentic AI refers to artificial intelligence systems that can independently analyze information, make decisions, and learn from experience, rather than just passively responding to commands.
We’re seeing a shift from passive large language models toward intelligent systems that can reason, act, and remember — systems that don’t just respond to prompts, but collaborate with clinicians, sift through fragmented histories, and flag what might otherwise be missed. Traditional generative AI is limited in that it typically handles only individual tasks and reactive workflows, lacking the ability to manage complex, multi-step processes. In contrast, agentic systems and AI agents are designed to coordinate multiple tasks, integrate external tools, and exhibit a more autonomous, orchestrated nature within veterinary care.
It’s already happening:
Hippocratic AI is building safe, conversational healthcare agents designed to handle low-risk, high-volume medical tasks — think pre-op instructions or chronic disease follow-up
Google’s Med-PaLM 2 is trained to reason across structured medical data and unstructured notes, scoring impressively high on medical licensing exams
OpenAI and Penda Health recently piloted an AI clinical copilot that helps clinicians in under-resourced clinics in Kenya assess, triage, and guide care.
These aren’t just digital assistants. They’re specialized agents working in coordination — each one focused on a different aspect of care, connected through memory and orchestration. The nature of agentic systems enables dynamic decision-making and seamless integration across workflows, allowing AI agents to operate autonomously and collaboratively within complex veterinary ecosystems.
So here’s the obvious question:
Why don't we offer the same to animals?
Veterinary medicine is decades behind. A recent survey found that over 60% of veterinary clinics still rely on paper records, making it difficult to track long-term health trends in pets. These inefficiencies increase operational cost for a veterinary practice and make it harder to improve consistency in care and focus on improving outcomes for patients. Your dog’s ALT has been rising for 18 months — but no one noticed, because the data was buried in a scanned PDF. Your cat had an abnormal thyroid value last year — but that chart lived in a different clinic’s system. Your horse’s electrolyte issues? Mentioned once during a phone consult, never written down.
Unlike human care, where data is at least centralized (albeit clunky), veterinary records are:
Dispersed across clinics, platforms, and formats
Largely unstructured and inconsistent
Missing longitudinal visibility — most systems show snapshots, not stories
Even academic research confirms this gap. A 2023 study published in Frontiers in Veterinary Science noted that “veterinary data is highly heterogeneous, often incomplete, and rarely available in a standardized format suitable for modeling.”1 Meanwhile, diagnostic AI research in veterinary medicine is still relatively narrow — mostly focused on radiology or specific disease classification, not systemic reasoning.
Medical Records
Notes, labs, meds — structured or not.
AI Health Summaries
Understand your pet’s health with smart, lifetime-based insights.
Track Progress
AI connects actions to outcomes over time.
Connected Pet Data
Agents analyze and link health data for deeper insights.
Personalized Care
Tailored recommendations — no guessing needed.
Vet in the Loop
Triage your pet’s cases that require a vet’s validation or touch
Security and Ethics
As agentic AI becomes an integral part of veterinary clinics, the importance of security and ethics cannot be overstated. These intelligent systems handle sensitive pet health data, manage complex workflows, and support critical decision-making for both veterinary teams and pet owners. To maintain trust and ensure operational reliability, veterinary medicine must prioritize ethical considerations and robust security protocols at every stage of AI adoption.
Agentic AI refers to artificial intelligence that can independently initiate tasks, analyze data, and make decisions—often without direct human intervention. This autonomy brings powerful capabilities, such as automating manual tasks, improving client communication, and delivering detailed information to support veterinary teams. However, it also introduces new challenges: ensuring compliance with data privacy laws, preventing unauthorized access, and maintaining transparency in how decisions are made.
A comprehensive suite of security measures is essential for protecting sensitive information and ensuring that agentic AI systems operate within established guidelines. Human oversight remains a cornerstone of ethical AI deployment, providing the necessary checks and balances to guarantee that technology supports, rather than overrides, veterinary expertise. By embedding governance policies and regular testing into their strategy, clinics can identify potential risks, manage high-level goals, and control the integration of agentic AI with existing software and lab systems.
In the real world, agentic AI acts as a force multiplier for veterinary teams—streamlining follow-ups, managing SOAP notes, and analyzing data to improve accuracy and consistency. These systems help address staff shortages and meet the higher expectations of today’s pet owners, all while enhancing patient outcomes and operational reliability. For example, agentic AI can automatically flag compliance issues, ensure timely follow-ups, and provide actionable insights that support both clinical and administrative workflows.
As veterinary clinics expand their use of agentic AI, it is crucial to create a framework that balances technological innovation with ethical responsibility. This means focusing on transparency, ongoing human oversight, and a commitment to compliance—building confidence in AI-driven care for pets and their owners. By doing so, the future of veterinary medicine will not only be more efficient and consistent, but also safer, more ethical, and truly centered on the well-being of every animal.
At CompanAIn, we're changing that.
We’re building agentic technology for animal care — AI that doesn’t just see the latest lab result, but knows the context behind it. Learn how AI for pets provides longitudinal health tracking, breed-specific insights, and actionable care recommendations that empower both veterinarians and pet owners. Knows your pet’s breed and history. Knows what changed, and why it matters. Knows how to respond in a way that’s clear, relevant, and grounded in the full picture.
We’re building technology that does more than respond — it remembers, interprets, and guides care over time. The system has the ability to evaluate information and adapt its actions based on ongoing interaction with users, including both veterinarians and clients, ensuring decisions are context-aware and responsive to real-world needs.
Lab results are translated using species — and breed-specific norms, paired with historical comparisons to highlight meaningful shifts
Health data is automatically structured into a living timeline, giving pet owners and vets a longitudinal view of labs, notes, medications, and observations
Subtle changes are proactively flagged — not just when a value exceeds a threshold, but when something looks off for your animal, based on past patterns
Pet owners can log real-time observations and ask natural-language questions — with responses that reflect the pet’s full medical context, not just the most recent input
The platform enables users to generate a personalized care plan, supporting veterinary teams and clients with clear, actionable steps. This structured approach helps build confidence in AI-driven recommendations by providing transparency, explainability, and proven value in everyday veterinary workflows.
Caper
Recurring inflammation
In early trials, CompanAIn helped a pet owner spot a pattern of recurring inflammation in their companion animal — a horse named Caper. Rather than attributing Caper’s discomfort to isolated incidents, the owner could see the bigger picture: connecting the dots between Caper’s history surfaced subtle but consistent signs tied to both his health and wellness. Acting on this insight, the owner adjusted Caper’s diet and replaced a once custom-fit saddle. The system helped maintain focus on the objective of improving Caper’s health and enabled rapid identification of recurring issues, ensuring timely intervention. At Caper’s next gait-analysis visit, the inflammation had resolved — an outcome that would have been missed without AI-powered longitudinal tracking.
We’re not here to replace veterinarians. We’re here to amplify their insight and bridge the gap between visits — using AI to ensure no red flag, no pattern, no meaningful change is missed just because it was hiding in a PDF.
Veterinary care deserves more than guesswork and gut checks. Pet owners deserve more than transactional visits and vague reports. Animals — who can’t speak for themselves — deserve a system that can.
This is agentic technology, built for veterinary medicine. And at CompanAIn, we’re making it real. Agentic AI supports veterinary practice by providing actionable insights, with leadership roles such as a senior director often advancing these innovations within the field.
Sources
1
Berman, J., et al
Data challenges in veterinary medicine: the path to machine learning
2
Google Research
Large Language Models Encode Clinical Knowledge
3
OpenAI
AI Clinical Copilot with Penda Health
4
Hippocratic AI
