Scaling AI for the Enterprise

2 minutes

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9 October, 2025

Just as Kubernetes reshaped cloud, Ray is redefining enterprise AI infrastructure. We dive into how AI tech leaders can use it to future-proof platforms, tame costs, and accelerate adoption at scale.

You’ll learn:

How enterprises are building AI platforms in-house to centralize governance while empowering product teams.
Why a foundational compute substrate (Ray) is critical for LLMs, multimodal AI, and reinforcement learning.
Open-source vs. managed services: where each wins for reliability, observability, and ROI.
Designing for heterogeneous compute (CPU/GPU) and preparing for multimodal workloads.
Enterprise adoption challenges: 95% of companies struggle to capture AI value—what leaders can do differently.
How to frame C-level outcomes—cost, scale, velocity—instead of drowning in stacks and logos.
Lessons from Uber, Spotify, Coinbase, and Fortune 500s on scaling from POC to production.

If you’re a CTO or senior engineering leader scaling AI beyond experiments, this conversation is your playbook for enterprise AI platforms that last.

Guests

Dawid Wang

Head of Marketing at Anyscale

Marketing executive who loves disrupting categories through impactful storytelling, messaging, and content. Proven in driving qualified pipeline in highly technical, competitive markets through a content and engagement growth strategy that drives interest every step in the buyer’s journey.

Engineer turned marketer with a 15+ year track record bringing emerging products to market and accelerating growth in highly competitive markets including AI/ML infra, databases, enterprise storage, data protection, and hyperconverged infrastructure. Love diving into technology, crafting the messaging that answers the why-what-how, and building the GTM engine that turns heads and rises above the competitive noise.

Jaikumar Ganesh

Head of Engineering at Anyscale

I am a seasoned technology executive with over 18 years of work experience in various domains, such as mobile, AI, and product companies. I have built and executed on high-performing teams across startups, hyper-growth companies, and large organizations.

Currently, I am the Head of Engineering at Anyscale, startup that makes distributed computing and scaling machine learning as simple as clicking a button.

My mission is to leverage technology to solve day-to-day problems and create value for users and businesses. I have extensive technical experience in Android, Location, Sensors, Applied Machine Learning, and Large Scale Distributed Systems. I have also contributed to several patents, publications, and awards, including the Google Founder’s Award for Android. In addition, I have founded and led a distributed engineering office, and advised and mentored startups and VC firms in New Zealand.