AI tool for the veterinary platform

The Aristek team helped a veterinary telemedicine platform owner enhance their practice management system with AI-driven automation, optimizing patient intake and appointment scheduling for seamless digital practice expansion.

Data science & AI Veterinary

USA

Veterinary

Summary
This case study explains how an AI-powered intake and scheduling tool was implemented for a veterinary telemedicine platform. The solution analyzes pet symptoms from text, photos, and videos to recommend the right specialist and automatically schedule appointments.

Developed as part of an AI veterinary software platform, the system helps clinics manage digital consultations and improve operational efficiency. In this material, we describe the system design, the implementation process, and the operational improvements achieved by veterinary clinics.

Key achievements

50%	reduction in front-desk workload
30%	faster client check-in
20%	better appointment utilization

Challenge

Re-examinations, consultations, and behavioral medicine are just a few areas where video consultations are useful. Pet owners often have minor questions that can be resolved in a short video call, allowing veterinarians to assess patients in their natural environment quickly.

However, the telemedicine platform owner noticed that many appointments were not urgent or required no further examination. Veterinary hospitals faced inefficiencies in patient intake and appointment scheduling, often leading to:

Mismatched scheduling that failed to account for a pet’s specific medical needs or specialist availability.
Incomplete or inaccurate intake information requiring additional clarification at check-in.
Increased workload for front-desk staff, reducing the time available for in-person client interactions.

Solution

To address the challenges listed above, the Aristek team proposed complementing the client’s telemedicine platform with an AI tool that would simultaneously handle unlimited requests and partially assist with initial consultations.

The system effectively acts as an animal hospital patient intake solution, helping clinics collect structured symptom data, analyze cases faster, and reduce administrative overhead.

AI was implemented to analyze common symptoms from the videos and photos provided, taking into account the existing medical history (given previous clinic visits). Other features of the technology also included:

1
The AI ensures that pets are matched with the right veterinary specialists (e.g., orthopedic experts for limping, dermatologists for skin issues, or cardiologists for breathing problems). This prevents unnecessary general consultations.
2
By analyzing medical history, symptoms, and videos together, the AI provides a comprehensive assessment instead of relying only on the owner’s description. Thus, it leads to better treatment recommendations rather than the owner would just browse the symptoms.
3
Instead of requiring the owner to manually search for an available vet, the AI can automatically schedule appointments based on urgency, specialist availability, and clinic hours.
4
Faster access to the right care means a higher chance of recovery and better long-term health for pets.
5
AI-assisted triage also helps detect severe conditions earlier, preventing complications.

Here are the key features of the AI-driven tool:

24/7 assistance
to provide instant preliminary assessments, even during weekends or after hours.
Smart scheduling to analyze symptoms and recommend time slots with the most relevant specialists.
Remote pre-screening
based on photos and videos taken by the owner to help them assess common issues like vomiting, coughing, allergies, or skin conditions before visiting a clinic.
Initial recommendations
for minor injuries or tick and flea infestations, reducing unnecessary visits.
Pre-visit guidance
with tailored instructions, such as fasting before specific procedures, ensuring pets are properly prepared for their appointments.

The following users benefit the most from this tool:

Veterinarians, technicians, and administrative personnel who manage patient intake, assessments, and scheduling.

Veterinary staff
Administrators and support staff optimizing workflow efficiency and resource allocation.

Hospital & clinic management
Individuals seeking quick preliminary assessments, appointment scheduling, and guidance on their pets’ health concerns.

Pet owners
External professionals using the platform for remote consultations, second opinions, and patient referrals.

Referring veterinarians & specialists

Project scope

While the AI-driven intake tool provides valuable preliminary assessments and recommendations, it cannot diagnose with 100% certainty. Its analysis is based on patterns, historical data, and clinical indicators, but it does not replace a professional veterinary examination.

The tool includes a mandatory disclaimer: AI is not infallible and may sometimes provide inaccurate assessments. Always consult a veterinarian for a definitive diagnosis and treatment plan, especially if your pet’s condition worsens or involves severe pain, difficulty breathing, or other urgent symptoms.

Before implementing the AI-powered veterinary assistance tool, the Aristek team thoroughly reviewed the project documentation to gain a deep understanding of the development context, existing data structures, and potential challenges.

This groundwork enabled a structured approach to data processing, ensuring accuracy and efficiency in the AI-driven solution.

The process unfolded as follows:

The development team gathered all available data on different animals, including medical history, symptoms, treatment outcomes, and behavioral patterns from various sources like veterinary records, owner reports, and previous consultations.
Since the collected data were often unstructured and inconsistent, the team organized, cleaned, and standardized them into a uniform format. This process ensured that key medical indicators, species-specific details, and treatment protocols could be easily compared and analyzed.
All the structured information was stored in a single, scalable data warehouse. This repository allowed real-time access to veterinary insights and enabled the collection of statistics for further analysis.
The AI module was trained using this comprehensive dataset to recognize patterns in symptoms, predict potential health issues, and recommend the most relevant specialists or treatments.
With the structured data, AI could assess new cases more accurately, suggest optimal appointment scheduling, and provide pet owners with tailored pre-visit instructions, streamlining the entire veterinary consultation process.
The team developed an AI tool where pet owners can describe their pet’s condition in detail through text or by uploading videos. The AI system could designed to analyze both written descriptions and visual cues, recognizing symptoms and movement patterns to provide accurate assessments and personalized recommendations efficiently.

How it works

When a pet owner notices something wrong with their pet – such as a limp, unusual coughing, skin irritation, or abnormal behavior – they can use the veterinary platform’s AI-driven intake tool to assess the situation quickly. That’s where the AI helper comes into play.

1
The system prompts the pet owner to record a video or take a photo of their pet’s condition – whether it’s a dog limping after a walk, a rash on the skin, excessive shedding, or labored breathing– to ensure a clearer assessment. They then describe the issue in their own words through the application form on the telemedicine platform.
2
The AI processes the submitted text, images, and videos, using an extensive database of past cases and clinical records. It evaluates factors such as gait patterns for mobility issues, visible swelling or redness for skin conditions, and other concerns. Unlike human experts, whose video diagnosis scores can vary based on subjective perception, AI applies standardized recognition criteria. For example, it can consistently assess the severity of lameness to ensure an objective analysis.
3
Based on its analysis, the AI provides initial insights into potential causes, whether it’s a mild strain, an early sign of arthritis, or something requiring immediate medical attention. The system also suggests the most relevant specialist and available appointment slots.
4
If a veterinary visit is needed, the AI asks if it’s needed to schedule an appointment with the most appropriate expert at the nearest available time. The system also provides tailored pre-visit instructions, such as keeping the dog from eating before certain exams to ensure the best possible diagnosis and treatment.
5
With every interaction, the AI refines its accuracy by learning from confirmed diagnoses and veterinary feedback, ensuring that future assessments become even more precise.

This AI-powered approach eliminates the guesswork for pet owners and saves time and money by allowing remote consultations and easy appointment booking. It also helps keep pets calmer by reducing unnecessary clinic visits.

For veterinarians, it helps prioritize urgent cases more efficiently, all while improving diagnostic objectivity.

Screenshots

Team

AI/ML Engineer x1
Front-end developer x1
Back-end developer x1
DevOps Engineer x2
Subject matter expert x1

Tools & technologies

GPT-4

OpenAI

PostgreSQL

TensorFlow

spaCy

AWS Lambda

FastAPI

AWS(ECS, RDS, ALB, CodeDeploy, S3, ECR)

Terraform

Docker

GitLab

Results

The AI-powered intake tool streamlined veterinary operations, optimizing patient triage and reducing administrative workload.

By introducing intelligent automation and modern AI vet tools, the platform helped veterinary clinics manage consultations more efficiently while improving patient intake and appointment scheduling.

The client noted:

50%	reduction in front-desk workload due to automated intake and scheduling
30%	faster check-in as clients arrived better prepared with complete intake details
20%	improvement in appointment utilization through optimized scheduling and resource allocation

Insights

Pet owners describe symptoms very differently from medical professionals
During early testing, many descriptions from pet owners were vague or emotional rather than clinical. The system had to be trained to interpret everyday language like “my dog seems weird today” and map it to potential medical signals.
Combining video analysis with written input improved triage accuracy
Text descriptions alone were often insufficient for reliable triage. When the system began analyzing photos and short videos together with the written description, its ability to recommend the correct specialist improved noticeably.
Automation helped clinics more than expected at the operational level
The initial goal was to improve the intake process, but the bigger effect appeared in scheduling efficiency. By matching symptoms with the right specialists automatically, clinics were able to reduce scheduling conflicts and use appointment slots more effectively.

Key takeaways

	Design AI systems to interpret non-medical language Pet owners rarely describe symptoms using clinical terminology.
	Use multiple input types for better triage accuracy Combining text, photos, and videos produces more reliable assessments.
	Keep the AI decision process transparent Clinics trust the system more when it clearly explains suggested specialists or urgency levels.
	Support existing workflows instead of replacing them AI intake tools should assist veterinarians and administrative staff rather than fully replace their processes.

AI tool for the veterinary platform

Summary

Key achievements

Challenge

Solution

Here are the key features of the AI-driven tool:

24/7 assistance

Remote pre-screening

Initial recommendations

Pre-visit guidance

The following users benefit the most from this tool:

Project scope

How it works

Screenshots

Team

AI/ML Engineer x1

Front-end developer x1

Back-end developer x1

DevOps Engineer x2

Subject matter expert x1

Tools & technologies

Results

Insights

Pet owners describe symptoms very differently from medical professionals

Combining video analysis with written input improved triage accuracy

Automation helped clinics more than expected at the operational level

Key takeaways