AI-assisted reasoning for modern veterinary practice

How Djuripedia works in a Clinical Setting

What Is Djuripedia at the clinic?

Artificial intelligence can’t replace clinical judgment — but it can strengthen it.
Djuripedia’s professional tools, led by AIVET PRO, are designed to support veterinarians, nurses, and researchers in their daily work by combining rapid data interpretation with structured reasoning.

AI doesn’t make decisions — it helps you make better ones.

Step 1

Collect and Describe Case Data

Input can come from anamnesis notes, free text, structured fields, or voice transcription.
The AI converts that information into a consistent clinical context — recognizing key findings, symptoms, and parameters such as:

species, breed, age, and weight
presenting complaints and relevant history
test results, medications, or previous diagnoses

The result is a structured digital case summary, ready for further reasoning.

Step 2

Reasoning and Differential Suggestions

Once the data is structured, the AI runs probabilistic pattern analysis and returns:

A list of possible differentials ranked by likelihood
Supporting reasoning (why each condition fits the input)
Rule-out logic (what doesn’t match)
Red-flag alerts for high-risk findings or urgent care

These outputs are never deterministic — they’re reasoning scaffolds for you to verify through examination and testing.

Think of AIVET PRO as a tireless intern that organizes your thoughts and never forgets a differential.

Step 3

Recommended Next Steps

The AI can propose next-level actions such as:

Diagnostic tests or imaging that would confirm or exclude key hypotheses
Suggested lab panels (hematology, chemistry, or hormonal)
Non-urgent monitoring plans for mild cases

Clinicians decide which steps are appropriate — the AI simply helps to prioritize them logically.

Step 4

Image and Lab Interpretation Support

AIVET PRO can analyze and comment on uploaded images or lab results:

Detects visible abnormalities (skin, dental, wound, etc.)
Highlights out-of-range values and pattern correlations
Suggests possible interpretations for review

All outputs are assistive, not diagnostic.
They help identify where to focus attention, not what to conclude.

Step 5

Communication and Documentation

After reasoning is complete, the AI can generate:

A summary for the patient record
A plain-language explanation for the client
A list of recommended next actions

This saves time and improves transparency in both client communication and professional reporting.

Clinical Control and Safety

We believe AI in animal health must be transparent and responsible.

Our systems are reviewed by licensed veterinarians.
We never replace professional judgement.
All data is handled according to GDPR and stored securely.

Learn more about AI Safety

The Future of Veterinary Reasoning

AI is not here to replace expertise.
It’s here to make professional reasoning faster, safer, and more structured.
Our long-term goal is to integrate seamlessly with electronic health records, laboratories, and educational platforms — creating a connected ecosystem where humans and AI collaborate for better animal health.