Today, Emily Sands, head of data and AI at Stripe, joins The Cognitive Revolution to discuss how the company built a payments foundation model that processes tens of billions of transactions into dense embeddings, exploring the technical architecture behind fraud detection improvements and the modular approach that enables rapid deployment of AI across Stripe's $1.4 trillion payment network.

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Today, Emily Sands, head of data and AI at Stripe, joins The Cognitive Revolution to discuss how the company built a payments foundation model that processes tens of billions of transactions into dense embeddings, exploring the technical architecture behind fraud detection improvements and the modular approach that enables rapid deployment of AI across Stripe's $1.4 trillion payment network.

Check out our sponsors: Google Gemini Notebook LM, Linear, AGNCY, Claude, Oracle Cloud Infrastructure.

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- Stripe's Scale: Processes $1.4 trillion annually, serving both small businesses and large enterprises (over half of Fortune 100 companies).
- Business Growth Impact: Businesses using Stripe grew 7x faster than the S&P 500 last year through optimizations across the payments lifecycle.
- Payments Foundation Model: Stripe has developed a domain-specific foundation model that converts transactions into vector embeddings, creating a specialized AI for the payments ecosystem.
- Data Advantage: Stripe's competitive edge comes not just from data volume (1.3 trillion annually, growing 38% YoY) but from the compounding feedback loop where better models deliver more value to businesses, driving further growth.
- "Business in a Box": There's emerging potential for AI to handle end-to-end business creation, including selection of third-party tools, payment providers, and other essential services.
- AI Company Partnerships: Two-thirds of the Forbes AI 50 companies already run on Stripe, as they focus on helping AI companies monetize effectively and scale globally.

Read the full transcript: https://storage.aipodcast.ing/...

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CHAPTERS:
(00:00) Sponsor: Google Gemini Notebook LM
(00:31) About the Episode
(05:49) Introduction and Context
(08:16) Payments Foundation Model
(16:22) Multi-Entity Transaction Patterns (Part 1)
(20:09) Sponsors: Linear | AGNCY
(22:42) Multi-Entity Transaction Patterns (Part 2)
(24:47) Model Architecture Details
(34:02) Ground Truth Challenges (Part 1)
(38:45) Sponsor: Oracle Cloud Infrastructure
(39:55) Ground Truth Challenges (Part 2)
(45:24) Iteration Loop Optimization
(54:32) Multimodal AI Applications
(01:05:11) Building on Stripe
(01:11:54) Agentic Commerce Evolution
(01:16:16) Platform Competition Dynamics
(01:20:42) Outro

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