AI & Knowledge Management
Human Expertise + AI Intelligence = Better Animal Care
V.E.T.S. is building the world's most comprehensive animal care knowledge base - 17+ years of data, 36,553 animals, 15,077 medical records. Now we're adding AI to help organize, search, and learn from this collective wisdom while keeping human expertise at the center.
The Foundation: 17+ Years of Data
V.E.T.S. has been collecting structured animal care data since 2008. This isn't random data - it's professionally managed, expertly curated, and covers every aspect of animal health and management.
36,553 Animals
Complete lifecycle data across 10 species, 747 breeds. Birth to death, every medical event, every performance record.
15,077 Vaccination Records
Which vaccines work, when they're needed, breed-specific responses, adverse reactions.
1,143 Diagnostic Images
X-rays, ultrasounds, DICOM-standard medical imaging with linked diagnoses and outcomes.
29 SOAP Note Types
Structured medical records covering routine care, emergencies, surgery, reproduction, dentistry, and more.
66 Active Herds
Commercial livestock operations providing breeding, performance, and economic data at scale.
11,928 Active Users
Veterinarians, livestock managers, pet owners, researchers - diverse perspectives and use cases.
This is the training dataset for the future of animal care AI.
Knowledge Management Today
TreeValues: Hierarchical Classification
TreeValues provide flexible, hierarchical organization of knowledge - think of them as customizable taxonomies for any domain.
Example: Horse Breeds TreeValue
Structure:
- Horses
- Breeds
- Quarter Horse
- Thoroughbred
- Arabian
- Paint
- Appaloosa
- Disciplines
- Racing
- Jumping
- Dressage
- Western Performance
Usage: Classify animals, organize medical records, structure product catalogs, build navigation menus.
Items: Rich Documentation
Items are detailed documentation attached to TreeValue nodes - rich text, images, videos, PDFs, external links.
Example: Quarter Horse Breed Item
Content:
- Breed history and characteristics
- Common health issues (HYPP, PSSM)
- Performance expectations by discipline
- Breeding recommendations
- Nutrition guidelines
- Training best practices
Collaboration: Multiple contributors add knowledge, version history tracked, peer review optional.
AI Vision: Where We're Headed
Phase 1: Embedded AI Recommendations (2025-2026)
Smart Data Entry
Vision: AI suggests breed, predicts weight ranges, auto-completes common fields based on species/breed/age.
Training data: 36,553 animals with complete profiles
Value: Faster, more accurate data entry
Health Pattern Recognition
Vision: AI identifies potential health issues based on symptoms, breed, age, history.
Training data: 15,077 vaccination records, 29 SOAP note types, diagnostic images
Value: Earlier intervention, better outcomes
Vaccination Intelligence
Vision: AI recommends vaccination schedules based on species, breed, location, risk factors.
Training data: 15,077 vaccination records with outcomes
Value: Optimized protection, reduced over-vaccination
Breeding Recommendations
Vision: AI suggests optimal breeding pairs based on genetics, performance, conformation, health history.
Training data: Multi-generation pedigrees, performance data, health records
Value: Improved genetics, healthier offspring
Permission Optimization
Vision: AI suggests optimal permission structures based on your organization type and collaboration patterns.
Training data: 11,928 users across diverse organizations
Value: Better security, easier setup
TreeValue Intelligence
Vision: AI helps organize TreeValues, suggests connections, identifies gaps, recommends structure improvements.
Training data: Existing TreeValue hierarchies and usage patterns
Value: Better organization, easier navigation
Phase 2: Natural Language Interface (2026-2027)
Conversational Search
Vision: "Show me all horses with colic in the last 6 months" - AI translates to database queries.
Implementation: LLM integration with database schema understanding
Voice Data Entry
Vision: Field veterinarians dictate SOAP notes, AI structures data, extracts entities, creates records.
Implementation: Speech-to-text + NLP + structured data extraction
Smart Reports
Vision: "Generate a breeding performance report for the last year" - AI creates comprehensive analysis.
Implementation: Data analysis + natural language generation
Phase 3: Collaborative Knowledge Building (2027-2028)
Automated Item Creation
Vision: AI generates draft Items for TreeValue nodes based on medical literature, user data, expert contributions.
Human role: Review, edit, approve, augment AI-generated content
Knowledge Gap Identification
Vision: AI identifies areas where documentation is lacking, suggests topics for community contribution.
Result: Comprehensive, continuously improving knowledge base
Cross-Reference Intelligence
Vision: AI suggests links between related Items, identifies conflicting information, recommends consolidation.
Result: Well-connected, internally consistent knowledge
Community Contributions
Vision: Users contribute knowledge, AI helps organize, peer review validates, everyone benefits.
Result: Wikipedia-like knowledge base for animal care
Phase 4: Predictive Analytics (2028+)
Disease Outbreak Prediction
Vision: AI identifies disease patterns across herds/regions, predicts outbreaks, recommends preventive action.
Data: 17+ years of health records, geographic patterns, seasonal trends
Performance Prediction
Vision: AI predicts animal performance based on genetics, early indicators, environmental factors.
Data: Multi-generation pedigrees, performance records, management practices
Economic Optimization
Vision: AI recommends management decisions to optimize profitability - breeding, culling, feeding, marketing.
Data: Financial records, performance data, market trends
Design Principles: Human-Centered AI
Core Principles
1. AI Suggests, Humans Decide
AI provides recommendations, professionals make final decisions. Expertise always paramount, AI enhances rather than replaces judgment.
2. Transparent & Explainable
AI explains its reasoning. "I recommend this vaccine because similar animals in your region showed X% better outcomes." No black boxes.
3. Continuously Learning
AI improves with every interaction. User feedback (accepted/rejected recommendations) trains better models.
4. Privacy-Preserving
AI learns from aggregate patterns, not individual records. Your data remains private while contributing to collective intelligence.
5. Collaborative, Not Competitive
Open knowledge base benefits everyone. Rising tide lifts all boats - better animal care for all.
Freemium Model: AI Features
Free Tier
- Basic TreeValues and Items (view, search, navigate)
- Community-contributed knowledge access
- Simple recommendations (breed-appropriate vaccines, basic health alerts)
Premium Tier
- Advanced AI recommendations (breeding optimization, performance prediction)
- Natural language search and queries
- Voice data entry and transcription
- Custom TreeValue structures with AI organization assistance
- Predictive analytics and trend identification
- Priority access to new AI features
- Organization-specific knowledge bases
- API access for custom AI integrations
Technical Approach
Embedded LLMs
Integrate leading AI models (GPT, Claude, Llama) via APIs. Not building models from scratch - leveraging best available technology.
Fine-Tuning
Train models on V.E.T.S. specific data (with user permission). Domain-specific knowledge for better recommendations.
Vector Databases
Semantic search across Items, SOAP notes, medical records. Find related content by meaning, not just keywords.
Real-Time Processing
AI recommendations appear as users work. Instant suggestions, no waiting for batch processing.
Join The Journey
We're building this together. V.E.T.S. is committed to transparent development, community input, and collaborative knowledge building.
Get involved:
- Use the platform: Your data (with permission) helps train better models
- Contribute knowledge: Add Items, edit TreeValues, share expertise
- Provide feedback: Tell us what AI features would help you most
- Partner with us: Research institutions, AI companies, domain experts welcome