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Source document· May 16, 2026

Starbucks Corporation Announces Early Results and Upsizing of its Tender Offers for Eight Series of Notes

View original at finance.yahoo.com
“4.800% Senior Notes due 2030 | 855244BL2/US855244BL23 | $500,000,000 | $600,000,000 | 1 | —— | $321,824,000”
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What we drew from this source

The claims Via News extracted from this document. We point to the source; we don't replace it.

  • The 4.500% Senior Notes due 2048 are subject to an aggregate principal amount sublimit of $200,000,000

    60% confidence
  • Except as described in the May 16 press release, the terms and conditions of the Tender Offers set forth in the Offer to Purchase remain unchanged

    60% confidence
  • $2,598,857,000 aggregate principal amount of the Notes were validly tendered prior to or at 5:00 p.m. Eastern Time on May 15, 2026 and not validly withdrawn

    60% confidence
  • Because the aggregate purchase price of tendered Notes exceeds the Aggregate Cap and Maximum Amounts, Starbucks does not expect to accept any further tenders of Notes

    60% confidence
  • Starbucks increased the Aggregate Cap for all Notes to $1.3 billion, the Pool 1 Maximum Amount to $600 million, and the Pool 2 Maximum Amount to $700 million

    60% confidence

Data points we hold from this source

Starbucks Corporation · principal tendered2598857000 USD
Starbucks Corporation · debt5000000000 USD
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AI Capital Surge: Late-August 2026 Funding Wave Spans Fintech, Enterprise Agents, and Robotics
A dense cluster of funding rounds landing on 2026-08-28 — from identity/fraud fintech player Socure ($156M plus its acquisition of Fravity) to enterprise AI agent startups (Instinct, Generalist AI, Owner), model infrastructure (Stability AI, Emerald AI), and autonomous logistics/aerospace (Gatik, Regent Craft) — signals investors are rotating aggressively into AI-native companies with demonstrable ROI, especially in financial risk/compliance and back-office automation. Parallel signals (Multiverse Computing's compression benchmarks cutting inference cost/latency, and Arkestro/CloneOps.ai publishing hard savings and labor-displacement figures) suggest the funding is chasing efficiency and measurable economic impact rather than pure model scale.
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ING Group
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