Frequently Asked Questions For Professionals

The next generation of veterinary decision support

Artificial intelligence is entering clinical veterinary practice — not to replace the veterinarian, but to extend professional capability.
At Djuripedia, we develop AI tools that support reasoning, documentation, and case preparation through structured data analysis and predictive modeling.

AI can already match or exceed human performance in certain analytical tasks — but it still requires clinical interpretation and accountability.
The following FAQs explain how to use Djuripedia’s AI responsibly and effectively within a professional workflow.

What is AIVET PRO?

AIVET PRO is a decision-support system for veterinarians and clinical staff.
It analyzes text, laboratory data, and images to propose differential diagnoses, highlight red-flag findings, and recommend next diagnostic or therapeutic steps.
It is designed to support clinical reasoning, not to issue autonomous medical judgments.

How reliable?

How reliable is AIVET PRO compared to a veterinarian?

In controlled testing, AIVET PRO can reach diagnostic agreement with experienced clinicians in many common scenarios and sometimes detect overlooked possibilities.
However, it can also misinterpret incomplete or ambiguous data.
Its value lies in generating structured differentials and second-opinion reasoning, not in replacing professional evaluation.

Treat AIVET PRO as a colleague who never gets tired — but who still needs supervision.

Can it improve my workflow?

How does AIVET PRO integrate into workflow?

Before consultation: summarizes anamnesis and patient history.
During consultation: provides probable differentials and relevant test suggestions.
After consultation: assists with discharge notes, summaries, and owner communication.

Integration can be API-based (EHR, lab, or imaging systems) or used stand-alone through Djuripedia’s secure interface.

And what about diagnostic data?

Can AIVET PRO interpret laboratory or imaging data?

Yes — it can process numerical lab results and uploaded images.
It detects abnormal patterns, compares values to species-specific ranges, and suggests additional panels or imaging when appropriate.
However, contextual interpretation remains the clinician’s responsibility.
Poor image quality or incomplete data can lead to misleading suggestions.

Are the clinical data protected?

How is clinical data protected?

All data are encrypted in transit and at rest, stored within GDPR-compliant infrastructure.
Case data are anonymized for system improvement and are never shared for marketing or third-party profiling.
Clinics maintain ownership of their case information.

What about differential diagnosis?

How does AIVET PRO perform differential diagnosis?

The model maps presented findings to likely disease patterns, scoring each differential based on probability and consistency with input data.
It also considers rule-out logic — conditions that are inconsistent with available evidence.
This reasoning is probabilistic, not deterministic; clinicians must verify results through examination and testing.

Can it made up information?

What about hallucinations or false confidence?

Large language models can generate plausible but inaccurate statements — known as hallucinations.
AIVET PRO minimizes this through prompt engineering, validation sets, and ongoing monitoring, but it can still occur.
The system labels speculative statements and encourages clinicians to cross-check.
Users are urged to report unsafe or clearly false responses to safety@djuripedia.com.

Transparency

How should clinicians communicate AI-supported results to clients?

Transparency builds trust.
Explain that AI assists in organizing and comparing information but does not make final decisions.
Clients generally appreciate knowing that technology supports — not replaces — their veterinarian’s judgment.

AI is the microscope for information — the veterinarian remains the interpreter.

Vision

What is Djuripedia’s vision for professional AI?

To create evidence-based, explainable, and ethical tools that strengthen veterinary medicine.
Our next phase will integrate a patented framework for even higher diagnostic accuracy, accountability, and traceability of AI reasoning.