このポッドキャストについて 🔗
Welcome to The AI Adoption Playbook—where we explore real-world AI implementations at leading enterprises. Join host Ravin Thambapillai, CEO of Credal.ai, as he unpacks the technical challenges, architectural decisions, and deployment strategies shaping successful AI adoption. Each episode dives deep into concrete use cases with the engineers and ML platform teams making enterprise AI work at scale. Whether you’re building internal AI tools or leading GenAI initiatives, you’ll find actionable insights for moving from proof-of-concept to production.
ホスト:
更新頻度:
every 16 days
平均音声長:
41 minutes
ゲストインタビュー
英語
アメリカ合衆国
15 エピソード
2025年1月7日から
episodic
最新エピソード 🔗
David Gildea has learned that traditional security models collapse when AI agents start delegating tasks to 50 or 60 other agents in enterprise workflows. As VP of Product for AI at Druva, he's building deterministic security harnesses that solve the authentication nightmare of multi-agent systems …
以前のエピソード 🔗
The fastest path to production AI isn't perfect architecture, according to Alexander Page. It's customer validation. In his former role of Principal AI Architect at BigPanda, he transformed an LLM-based prototype into "Biggy," an AI system for critical incident management. BigPanda moved beyond bas…
UCHealth’s healthcare AI methodology currently enables 1 nurse to monitor 14 fall-risk patients, with plans to scale to 140, then 1,400 through computer vision and predictive analytics. Instead of exhausting pilots, they deploy in phases: test, prove, optimize, then scale. This has created a system…
The construction industry sits on goldmines of unstructured data that could revolutionize how buildings get built. From thousands of contracts to communication logs spanning 12-36 month building cycles, Dan Williamson, Director of Artificial Intelligence at Ryan Companies US, says all that data rem…
At Elastic, CISO Mandy Andress learned that pragmatic guardrails work better than blanket bans for managing AI adoption across their 3,500-person distributed workforce. Instead, she enables AI tools with smart controls rather than block them entirely.
As both a customer and provider in the AI ecos…
At Yext, evaluating every AI tool through a security-first lens sparked comprehensive AI governance frameworks that protect enterprise data without stifling productivity.
Rohit Parchuri, SVP & CISO, explains how they developed "AI fact sheets" for these evaluations, comparing each tool against…
What happens when you build AI agents trusted enough to handle production incidents while engineers sleep? At Datadog, it sparked a fundamental rethink of how enterprise AI systems earn developer trust in critical infrastructure environments.
Diamond Bishop, Director of Eng/AI, outlines for Ravin …
How do you achieve 75% weekly active AI tool usage across an enterprise? At UserTesting, it started with a deliberate strategy to foster experimental adoption while maintaining governance guardrails. Michael J. Domanic, Head of Generative AI Business Strategy, tells Ravin their approach to transfor…
When technical systems fail at companies like Netflix or Etsy, every minute of downtime can cost millions. That's why incident.io is building AI systems that can automatically investigate and diagnose technical problems faster than human engineers.
In this episode of The AI Adoption Playbook, Lawr…
What happens when AI capabilities outpace organizational readiness? At Shopify, this tension has pushed them to develop a practical implementation approach that balances rapid experimentation with sustainable value creation.
Spencer Lawrence, Director of Data Science & Engineering, shares how…
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