[Invite-only] Beyond Hack #5 - From Data Access to Deployment: What It Really Takes to Build AI for Healthcare

​Beyond Hack Meetup (40 pax) — Founder × Talent × Investor x Mentor

​Hosted by Siriraj x MIT Hacking Medicine
Sponsored by 0.1 Ventures

📍 ZenicHub Cowering Space (BTS Asoke / Paid Parking Available) | ⏱️ 3 hours | 🎟️ Limited to 40 seats (invite-only)

​Beyond Hack is a monthly, highly curated meet-up for people building (or aspiring to join) a healthtech startup in Thailand and Southeast Asia. The event designed to create real outcomes: teams formed, pilots unlocked, and startups shaped into investment- and grant-ready companies.

​This month’s featured speaker - Ronnachai Jaroensri (Tiam)

​Khun Ronnachai Jaroensri (Tiam) - a lecturer at Siriraj Hospital, MIT PhD in Computer Science, and former Google Health researcher, he works at the intersection of computer vision, multimodal AI, and real-world clinical deployment. At Google Health, he worked on advancing the medical multimodal capabilities of Gemini and Gemma, with a focus on vision-language systems that enable more natural and effective interaction between AI and users. Now based in Thailand, he is passionate about translating AI from research into healthcare practice and helping grow a stronger community of AI researchers in Thailand.

​Topic: From Data Access to Deployment: What It Really Takes to Build AI for Healthcare

​A practical fireside chat on what it really takes to build AI for healthcare in the real world. Drawing from experience across MIT, Google Health, and now Thailand’s healthcare ecosystem, this conversation will explore the journey from cutting-edge AI research to the realities of clinical data access, validation, workflow integration, and deployment. We will unpack not just how strong models are built, but what it takes for healthcare AI to become trusted, adopted, and useful in practice.

​Some questions we’ll cover

• ​What does “data access” in healthcare actually mean in practice, and why is it often much harder than founders expect?

• ​What looks different about the real opportunities and constraints of applying AI in healthcare in Thailand?

• ​What does “data access” actually mean in healthcare, and what makes it so difficult to turn messy real-world clinical data into something usable for AI?

• ​What do clinicians, hospitals, and health systems need to see before they are willing to trust and adopt an AI product?

• ​What is the gap between building a model that performs well in testing and building a product that actually works in clinical workflows?

• ​Where do promising healthcare AI products usually get stuck on the path from pilot to real deployment?

• ​Having worked in healthcare AI since the pre-GPT era, what has fundamentally changed, and what challenges remain the same?

​Objective

​What we’re trying to achieve (12-month objective)

• ​Get startups to become grant-ready / investment-ready and successfully raises support from the NIA or investors

• ​Get talents to join early-stage founders as co-founders or founding team

​Who should attend

​Early-stage founders

• ​Looking for mentorship on strategy, fundraising, go-to-market, and hiring/cofounder matching

​People aspiring to join a startup (medical professionals developers, business & finance)

• ​Looking to join a team with momentum, clear mission, and real problems to solve

​Investors angels scouts

• ​Looking for early-stage dealflow and a room of founders who can execute

​Advanced founders / operators

• ​Already raised funds, built product, or selling to the market — here to share real lessons + help others avoid traps