Join CVS Health, Doordash, Spotify, Twilio and many others at MLW's HYBRID AI 2026 in San Francisco this May

Enterprise-Scale GenAI Frameworks: Automating Data Modeling, Validation, and Cloud Provisioning

Generative AI is redefining how enterprises design, deploy, and optimize data systems. This session explores a production-grade GenAI framework that automated data modeling, validation, and GCP infrastructure provisioning—reducing manual effort by 70% and accelerating release velocity by 40%. Attendees will learn how to design scalable GenAI pipelines, integrate LLMs with enterprise data workflows, and apply intelligent automation to streamline complex engineering tasks. Drawing from real-world deployment experience, this talk reveals actionable strategies for transforming AI innovation into tangible operational efficiency across large-scale data ecosystems.

More info here.

How Twilio Uses Its Own AI Builder to Transform Customer Conversations

Come learn about how Twilio’s AI assistant prototype tripled customer conversions and scaled to support 80 countries and 12 languages. Rikki will discuss real application of ML within Twilio’s functional environments to accelerate growth.

Twilio’s AI assistant inspired this article on genAI’s reliability layer by conference chair Eric Siegel: https://www.forbes.com/sites/e...

More info here.

Keynote: AI Transformation Hinges on Very Particular Organizational Requirements

Generative AI is not only great at generating artificial content, it is great at personalizing and recommending human-created content: from Music, to Videos, to Podcasts, to Audiobooks. Through the use of Large Language Models, we better understand the content creators created and the content consumers are interested in. This allows GenAI to find the best content for each user as well as give context on why this new content is relevant. Context can come from an AI DJ explanation or the right image or preview or trailer. By integrating world knowledge, content understanding and user understanding, LLMs provide a unique opportunity to craft what we call personal narratives—stories that resonate with listeners and familiarize them with recommendations.

More info here.

Agent-in-the-Loop: Continuous Learning Flywheel for Fraud Detection

Fraud detection systems often face unreliable ground truth due to costly and inconsistent human labeling. This session presents agent-in-the-loop framework, which uses large language models (LLMs) as intelligent labelers to power a continuous learning flywheel. The LLM integrates domain knowledge and historical data to generate high-quality labels, propose new predictive signals, and enhance model retraining. Through agent-in-the-loop feedback and quality controls, the system continually refines its understanding. Attendees will learn how adaptive LLM-ML systems can drive scalable and self-improving fraud detection models.

More info here.

See the Complete Agenda and speakers from these leading brands:

What's different about Hybrid AI 2026?

How can practitioners get genAI pilots to production – and get predictive AI from development to deployment – considering that the success rates are still extremely low?

Join the leading experts tackling these issues at HYBRID AI 2026. Take the opportunity to talk to them, as well as listen and and find the solutions to some of your key 2026 challenges in machine learning, hybrid AI and predictive analytics.

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