ThinkData Podcast

AI is everywhere in biotech, but where does it genuinely create impact?
In this episode of the ThinkData Podcast, I sat down with Josh Haimson, Co-Founder and CEO of Inductive Bio, to explore how AI-driven virtual chemistry labs are transforming drug discovery.
We cover:
Where AI truly outperforms traditional approaches in drug development
Why computational models are finally earning real trust from scientists
What Inductive Bio’s Series A unlocked, and how they’re balancing speed vs depth
The role of industry partnerships and early adopters in shaping the platform
Where are the biggest AI opportunities in drug discovery over the next 3–5 years

A grounded, technical, and refreshingly honest conversation about the future of AI-powered therapeutics.

Healthcare doesn’t struggle because of a lack of data or innovation.
It struggles because of admin.
In this episode of the ThinkData Podcast, I sit down with Matt Faustmen, Co-Founder and CEO of Honey Health, to explore why back-office operations are the real constraint in modern healthcare, and how autonomous AI agents can finally unblock them.
We talk about:
Why EHR add-ons and traditional automation fall short
How Honey Health decided which customers to go after first, and what they got wrong
What makes AI agents fundamentally different from workflow tools
Where Honey’s real competitive advantage comes from
And the company Matt is actually trying to build over the next five years

This is a grounded, operator-level conversation about building AI for real systems, real constraints, and real outcomes, not demos.
If you’re building in healthtech, AI infrastructure, or regulated industries, this one’s worth your time.

AI apps are exploding, but monetisation remains one of the biggest unanswered questions.
In this episode of the ThinkData Podcast, Mike Choi, Co-Founder of Koah Labs, shares how AI products can generate revenue without destroying user experience or trust.
We explore why classic ad models fail in chat-based interfaces, what it takes to convince AI builders and advertisers to adopt new monetisation approaches, and how advertising inside GenAI products will evolve over the next few years.
If you’re building, funding, or scaling an AI product, this episode is a must-listen.
🧠 Topics Covered
Why most AI apps struggle to monetise sustainably
The origin story behind Koah Labs
Why traditional advertising breaks in chat-based products
How to monetise AI without harming user experience
Convincing AI founders and advertisers to embrace new models
The future of advertising in GenAI over the next 2–3 years
Ethics, privacy, and trust in AI-powered ad systems

In this episode, we sit down with Ilya Levtov, Co-Founder and CEO of Craft, to unpack how AI is transforming supply-chain intelligence and risk management.
We explore Ilya’s unconventional journey from Juilliard to Goldman Sachs to venture capital, and ultimately to founding Craft, as well as why traditional data tools fall short when it comes to real-time supplier risk.
From government to healthcare, we dive into how leading organizations are using Craft to anticipate disruption, assess supplier exposure, and make faster, more confident decisions in an increasingly volatile world.

Today on the ThinkData Podcast, I’m joined by Arjun Vora, Co-Founder of Teambridge, a Series B startup redefining how frontline and hourly teams are managed.
Arjun previously led design on the Uber for Drivers app, an experience that gave him first-hand insight into how broken tools, poor communication, and rigid systems impact people who don’t sit at desks all day.
Teambridge is building a single operating system for frontline teams: combining scheduling, communication, workflows, and real-time insights into one intelligent platform. Their mission is simple but powerful, make managing people easier and make work better for the people doing it.
In this episode, we explore why frontline workers have been overlooked by technology, how AI can genuinely improve shift-based work, and where the biggest opportunities lie over the next few years.
🧠 Topics We Cover
The lightbulb moment behind Teambridge, and how Uber for Drivers inspired the idea
Why most AI tools still ignore frontline and hourly workers
How Teambridge applies AI to scheduling, communication, and workflows
The hardest challenges in scaling a two-sided workforce platform
Where AI will have the biggest impact on frontline work next