Rastro API
Best in class catalog enrichment and normalization with full traceability. Every field validated, sourced, and ready for production.
import requests
response = requests.post(
"https://catalogapi.rastro.ai/api/public/enrich",
headers={"Authorization": "Bearer YOUR_API_KEY"},
json={
"input": {"product_name": "McMaster 91251A123"},
"output_schema": [
{"name": "material", "type": "string"},
{"name": "thread_size", "type": "string"},
{"name": "price", "type": "number", "unit": "USD"}
]
}
)
print(response.json())Built for production
Every response includes sources, confidence scores, and audit trails.
Full Traceability
Every value includes sources and explanations.
{
"material": {
"value": "316 Stainless Steel",
"sources": ["https://mcmaster.com/..."],
"source_explanation": "From specs table"
}
}Automatic Error Flagging
Flags uncertain values for human review.
{
"review_info": {
"reasoning": "Conflicting specs",
"confidence": "medium",
"flags": ["verify_dimensions"]
}
}Taxonomy Prediction
Auto-classify into your category hierarchy.
{
"category_path": "Fasteners > Bolts",
"taxonomy_attributes": {
"Thread Size": "M10-1.5",
"Grade": "A2-70"
}
}Quality Scoring
1-5 readiness score for each item.
{
"quality_score": 4,
"quality_result": {
"explanation": "Complete specs",
"issues": ["No datasheet link"]
}
}Enrich API
Web research with citations. Pass a product and schema, get enriched data with sources.
View docs →Flows API
Visual data pipelines. Build workflows in the dashboard, execute via API.
View docs →Catalogs API
Managed product storage. Store items, then enrich with Flows or the Enrich API.
View docs →Start building today
Get API access and enrich your first product in minutes.