Tapestry is actively deploying AI/ML for core functions like customer acquisition, personalization, and pricing, supported by a 29% YoY increase in marketing spend to $962.5M.
Filing excerpt
During fiscal 2026, we continued to advance our artificial intelligence including predictive, generative and agentic models, as well as machine learning across key areas such as data analytics, planning, marketing, customer acquisition, personalization, pricing and product creation.
What this signalsFilings often name leadership changes, deals and spending plans.
Technologies
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This page shows a preview. The full sec-10k record in the Signal API and MCP can also have these 8 fields. Some fields are empty for some signals.
Company
linkedin_urlValue in the APIindustriesValue in the APIemployee_count_lowValue in the APIemployee_count_highValue in the APIrevenueValue in the APIdescriptionValue in the APISignal
signal_nameValue in the APIassociationValue in the APIGET /v1/signals/1528d2f0-db5d-4fa9-947f-a89c891fa9aa returns this record as JSON. POST /v1/companies/enrich returns every signal for tapestry.com.
{
"signal_id": "1528d2f0-db5d-4fa9-947f-a89c891fa9aa",
"signal_type": "sec-10k",
"signal_subtype": "aiInvestment",
"detected_at": "2026-08-18T07:04:33.493+00:00",
"company": {
"name": "Tapestry",
"domain": "tapestry.com"
},
"data": {
"detail": "Tapestry is actively deploying AI/ML for core functions like customer acquisition, personalization, and pricing, supported by a 29% YoY increase in marketing spend to $962.5M. This indicates budget for AI platforms, data infrastructure, and specialized talent.",
"metrics": {
"pct": 0.29,
"timeframe": "current_year",
"pct_context": "Year-over-year increase in marketing spend from FY2025",
"dollar_context": "Total marketing-related expenses in fiscal 2026",
"dollar_millions": 962.5
},
"summary": "Advancing predictive, generative, and agentic AI models for marketing and product creation.",
"excerpts": "During fiscal 2026, we continued to advance our artificial intelligence including predictive, generative and agentic models, as well as machine learning across key areas such as data analytics, planning, marketing, customer acquisition, personalization, pricing and product creation.",
"relevance": 0.8,
"sentiment": "positive",
"confidence": "high",
"source_url": "https://www.sec.gov/Archives/edgar/data/1116132/000111613226000018/tpr-20260627.htm",
"filing_date": "2026-08-13",
"filing_year": 2026,
"fiscal_year_end": "06/27",
"sales_relevance": "Target for AI vendors",
"signal_category": "technology",
"technologies_mentioned": [
"artificial intelligence",
"predictive models",
"generative models",
"agentic models",
"machine learning",
"data analytics"
]
}
}
curl https://signals.autobound.ai/v1/signals/1528d2f0-db5d-4fa9-947f-a89c891fa9aa \
-H "X-API-KEY: $AUTOBOUND_API_KEY"curl -X POST https://signals.autobound.ai/v1/companies/enrich \
-H "X-API-KEY: $AUTOBOUND_API_KEY" \
-H "Content-Type: application/json" \
-d '{"domain":"tapestry.com","limit":20}'Long text fields are shortened on this page.
Looking up one signal by its id is free. Enrich costs 2 credits per signal returned; a call with no results is free.