ANT for Health
Build health and medical AI applications with intelligent model routing. Supplement scanning, medical Q&A, clinical NLP, drug interaction analysis, and nutrition extraction — powered by the right AI model for every task.
The right model for every health task
ANT routes each request to the best model based on the task — OCR for scanning, vision for photos, reasoning for medical analysis.
Scan supplement labels, prescriptions, lab reports. Mistral OCR extracts text with high accuracy.
Analyze photos of supplements, food, skin conditions. Routes to the best vision model (Gemini, GPT-4o, Claude).
Complex medical reasoning — drug interactions, clinical analysis, diagnostic reasoning with chain-of-thought.
Enrich with real-time medical information. Search clinical databases, product databases, and medical literature.
Maximum quality for critical health decisions. Routes to the most capable model regardless of cost.
Intelligent default — simple health Q&A gets fast models, complex analysis escalates automatically.
Health AI use cases
Supplement Label Scanning
Photograph a supplement bottle. OCR extracts the ingredients, an LLM parses the nutritional facts, and web search enriches with brand info, dosage recommendations, and clinical data.
Medical Question Answering
Patients ask health questions in natural language. ANT routes simple queries to fast models and complex medical questions to frontier reasoning models that can provide nuanced, evidence-based answers.
Nutrition Analysis
Parse food labels, meal photos, or recipe text into structured nutritional data. Vision models identify food items, LLMs extract macro/micronutrient content, and search fills in database values.
Drug Interaction Checking
Analyze combinations of medications and supplements for potential interactions. Reasoning models cross-reference known interactions and flag concerns with citations.
Clinical Document Processing
Extract structured data from clinical notes, lab reports, discharge summaries. OCR handles scanned documents, LLMs extract entities (diagnoses, medications, dosages).
Health Chatbot / Virtual Assistant
Build conversational health assistants that triage symptoms, explain conditions, and provide wellness recommendations. Intelligent routing ensures medical questions get the most capable models.
Example: Supplement scanning pipeline
# Step 1: OCR — extract text from label photo
ocr = client.chat.completions.create(
model="ant:ocr",
messages=[{"role": "user", "content": [
{"type": "image_url", "image_url": {"url": photo_base64}},
{"type": "text", "text": "Extract all text from this supplement label"}
]}],
)
# Step 2: Parse + enrich — LLM with web search
parsed = client.chat.completions.create(
model="ant:best",
tools=[{"type": "ant:search"}],
messages=[
{"role": "system", "content": "Parse supplement data and search for missing info"},
{"role": "user", "content": ocr_text},
],
)
# Step 3: Vision fallback — if OCR failed
if not ocr_text:
fallback = client.chat.completions.create(
model="ant:vision",
messages=[{"role": "user", "content": [
{"type": "image_url", "image_url": {"url": photo_base64}},
{"type": "text", "text": "Analyze this supplement label directly"}
]}],
)Important: AI models can make mistakes. Health and medical applications built with ANT should include appropriate disclaimers and should not be used as a substitute for professional medical advice, diagnosis, or treatment. Always verify AI outputs against authoritative medical sources.
Build health AI with ANT
OCR, vision, reasoning, search — every capability through one API. $5 free credits to start.