A Live Conversation with Top 10 Pharma AI LeadershipBuild vs. Buy: Lessons from a Top 10 Pharma on their AI Journey

Every life sciences team can stand up a working AI demo in weeks. The hard part is proving it holds up under a clinician’s judgment and next quarter’s question, as one biopharma team learned firsthand.

Point a model at a data warehouse. Wire up a few agents. Within weeks, something is answering real questions in front of real executives. That part is easy. Proving the answer holds up, next quarter, under a clinician’s review and a compliance officer’s sign-off, is not.

One biopharma team learned that after nearly a year building its own solution in-house, then deciding what to keep building and where outside help earned its place. A Director of AI Agents at a Top 10 Pharma will share what she navigated and what she’d do differently. John Wollman, General Manager, Marmot at Komodo Health, adds the outside view on what makes a demo enterprise-ready.

Join us on September 24, 8:30am PT/11:30am ET to:

  • See exactly where a demo stops being enough, and a high-stakes decision needs more.
  • Hear one biopharma team’s real build-vs-buy call, made after building in-house for nearly a year.
  • Learn what “trustworthy AI” actually requires: grounded, explainable, reproducible, verified, and governed.
  • Get unscripted answers from both sides of the table: the builder and the buyer.

Register for the Webinar on September 24

Webinar FAQ

Confident and correct are not the same thing. An AI system can sound certain and still be wrong. In healthcare, that gap costs more than credibility. It costs a treatment decision, a mispriced risk, a compliance officer’s signature. Trustworthy AI closes that gap. Marmot is built on five pillars:

  • Grounded, tracing every answer back to a verifiable source of truth
  • Explainable, showing the work behind every step
  • Reproducible, so the same question returns the same answer, every time
  • Verified, checked systematically before a result ever reaches a user
  • Governed, with privacy, access, and compliance built in, not bolted on

Confident is easy. Trustworthy is earned.

Every AI program moves through the same test. Early on, the question is defensive: is this right? Can we reproduce it? Will it hold up under scrutiny? Mature programs have already answered that. The question turns offensive: what do we do with this? What should we ask next? That shift, from defending the answer to acting on it, is what an AI maturity model measures. The five pillars, grounded, explainable, reproducible, verified, and governed, are the markers. Meet more of them, keep meeting them as the models change, and a team moves further up the curve.

Yes, this webinar will be shared for on-demand viewing to all webinar attendees via email. It will also be available in our on-demand content library after the broadcast.