AI & Knowledge Management
The Philosophy Behind V.E.T.S.
At the heart of V.E.T.S. is a fundamental question: How do we combine the power of artificial intelligence with the irreplaceable value of human expertise to create the world's best animal knowledge base?
Knowledge vs. Intelligence
We distinguish between knowledge (the accumulation of facts, data, and information) and intelligence (the dynamic process of creating, observing, evaluating, and assessing those facts). Both humans and AI systems can accumulate knowledge. The magic happens when human intelligence and machine intelligence work together to curate, refine, and organize that knowledge.
How AI Helps Today
Currently, AI (specifically large language models) assists our development team in creating and improving content for the platform:
- Knowledge Base Development: AI helps our team draft and refine procedural descriptions, item definitions, and documentation
- Content Improvement: AI suggests ways to make technical content clearer and more comprehensive
- Consistency Review: AI helps identify gaps or inconsistencies in our knowledge base entries
- Multi-Language Support: AI assists with translations and ensuring terminology consistency across languages
Important: AI does not currently provide real-time assistance to end users. The platform's capabilities—evaluations, action tracking, inventory management, collaboration—are all built on traditional database architecture and user-driven workflows.
The Vision: Human-AI Collaboration
Our long-term vision is to create the world's best animal knowledge base through human-AI collaboration. We're exploring how AI could:
- Assist with Data Entry: AI could help users fill in common fields or suggest relevant information based on context
- Surface Insights: AI could identify patterns in evaluation data or health records that humans might miss
- Provide Recommendations: AI could suggest evaluation criteria, action items, or inventory needs based on historical data
- Answer Questions: AI could help users find information in the knowledge base more naturally
This vision requires careful implementation. AI must enhance human expertise, not replace it. The platform must remain reliable, predictable, and transparent in how it uses AI capabilities.
Why This Matters
The challenge in animal care is not lack of data—it's making sense of the data. Professional operations generate enormous amounts of information about individual animals, breeding outcomes, treatment effectiveness, and training progression. The goal is to organize this knowledge so that:
- Patterns become visible
- Best practices can be documented and shared
- Decision-making improves over time
- Institutional knowledge persists as people come and go
V.E.T.S. provides the structure for this knowledge accumulation today. AI represents one possible tool for making that knowledge more accessible and actionable in the future.
Current Focus: Building the best possible traditional database-driven platform. AI capabilities will be added thoughtfully when they genuinely enhance the user experience without compromising reliability or transparency.