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London is a hub for the world’s most well-known enterprises and organisations. Rev brings together data science and IT leaders at the cutting edge of AI innovation in industries such as financial services, life sciences, and media and entertainment.
Join us for direct conversations, success stories, and lessons learned on moving from AI experiments to production-grade systems with a lens on regulated industries.
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Enterprises have the models, the talent, and the budgets. What's missing is the operational foundation to turn AI investment into measurable business impact. Discover how a full enterprise AI application platform empowers teams to build, govern, and scale AI-powered decisioning systems.
Eduardo Arino de la Rubia of Central European University, and formerly Sr. Director of Data Science at Meta, will share how data science organizations and data scientist skillsets must evolve for the agentic era, and discuss diagnostics for calibrated confidence - in a time of multidimensional uncertainty.
Leading life science companies have deeply embedded Domino across the organisation, from benchmarking foundation models in clinical development to automating QC workflows. Learn how Domino's compliant environment became the foundation for rapid, grassroots AI adoption at enterprise scale.
AI amplifies what's already there—good or bad. Hear honest lessons from building two contrasting systems: a deterministic pricing engine and an agentic financial planning tool. Discover where AI genuinely elevates, where it amplifies chaos, and why governance and observability make all the difference.
Modernising a statistical computing environment is more than a technology upgrade. Discover how pharma companies are evolving legacy SCEs in regulated contexts—consolidating technical debt, containing scope, and building the right foundations across people, process, and IT.
The real AI bottleneck isn't the model—it's infrastructure. Hear first-hand lessons from building an enterprise data science platform across decentralised teams in analytics, risk, and audit, and learn why organisations consistently underestimate the skills and investment required to scale.
Regulated enterprises don't have a model problem—they have an application problem. See live examples of AI applications driving real business outcomes, not just proof-of-concepts, and learn how enterprises can build and deploy production-ready AI apps in hours, not weeks.
Vibe coding lowered the barrier; agentic engineering raises the stakes. As AI takes on full dev lifecycles, the challenge isn't autonomy—it's knowing when humans must stay in the loop. Learn to design HITL checkpoints, build governance, and scale toward dynamic virtual engineering teams.
Moving from fragmented infrastructure to a unified AI-powered platform that serves the world's largest brands is no easy feat. WPP will share their journey to build a client intelligence platform - covering data centralization, change management, and the next frontier: custom propensity models trained on client data, and AI-driven media activation.
As AI reshapes data science, BNP Paribas Cardif's AI Engineering team is enabling app-based, self-service AI. Learn how they developed a production-ready prototype of their verbatim analyzer, designed to process feedback from all respondent types. Powered by an LLM-enhanced hybrid engine combining generative AI and statistical modeling, this solution demonstrates how deploying app on Domino accelerates value delivery across the business.
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