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Why Capital One built its multi-agent AI platform around open-weight models
Presented by Capital One At VB Transform 2026 , Kel Vanee, MVP of machine learning engineering at Capital One, spoke with Sam Witteveen, Senior Technology Contributor at VentureBeat, about how the bank built a scalable multi-agent AI…
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At VB Transform 2026, Capital One’s machine‑learning engineering MVP Kel Vanee explained to VentureBeat senior contributor Sam Witteveen how the bank created a scalable multi‑agent AI architecture using heavily customized open‑weight models instead of a generic foundation model. Vanee traced the platform’s roots to earlier investments in data transformation and cloud adoption, which he said gave the firm the agility to respond to the current AI surge. Those foundations allowed Capital One to design a centralized, enterprise‑wide AI platform with built‑in governance, tailor open models with proprietary data, and develop its own multi‑agent orchestration layer.
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