WEBINAR

How to Build a Clinical Trial AI Strategy:
The Operational Intelligence Layer AI Needs

July 8, 2026 | 11 AM ET

Most clinical AI programs start in the wrong place.

They are being built on assumptions about how trials run, not how they actually run.

Join Florence CEO Ryan Jones for a practical discussion on why many AI initiatives struggle, where the missing operational data lives, and how to evaluate AI opportunities before committing budget.

Before you invest in another AI tool, learn how to:

  • Recognize the hidden operational gaps that limit AI performance and adoption
  • Decide where AI can drive measurable improvements in your trial operations
  • Build an AI strategy that is scalable, compliant, and aligned with how studies actually run

The work Florence AI is doing inside your trials today.

Specific capabilities, embedded in the Florence platforms you already use. No new logins. No parallel tools. No rip-and-replace.

Available now

Site Feasibility

The work: Faster, more consistent feasibility responses for research sites.

Site coordinators spend hours digging through old emails, spreadsheets, and PDFs to answer the same feasibility questions, over and over again, across every new study. Florence AI captures responses into a centralized library, then auto-populates answers when new questionnaires arrive. Coordinators review and submit in minutes instead of hours.

What it changes: Sites take on more studies without adding headcount. Sponsors get site selection decisions sooner. Feasibility stops being the bottleneck it has always been.

Where it lives: Inside the Florence platform sites already use.

Model Context Protocols

The work: More efficient prioritization in your clinical trials documentation.

AI agents integrated with Claude, ChatGPT, or your own solution securely query, analyze, and act upon “site reality” in real-time.

What it changes: Instantly cross-reference missing documents, skipped tasks, and study progress in real-time.

Where it lives: Inside the Florence platform you already use.

Early access

Document Intelligence Service

Workflow-aware document quality, classification, and analysis inside eBinders and eISF. Florence surfaces issues for human review before they become findings, turning inspection readiness into the default state instead of a fire drill.

Sponsor Site Navigator

Sponsors today can only afford to have a Clinical Research Lead (CRL) deeply qualify the top 20% of sites in a trial. Florence Navigator scales the CRL’s work across every site while the CRL reviews and approves every site decision. The same CRL covers three to five times as many sites in the same amount of time.

Coming soon

TrialFlo

Most trial delays are not caused by missing information. They’re caused by missing coordination.

TrialFlo transforms workflow activity into operational intelligence, helping teams identify stalled work, surface dependencies, and understand how trial execution is progressing in real time.

Budget Auditor

Florence estimates that sites lose $300m a year in missed billings. Flo Budget Auditor catches omitted billable events to ensure your site has the resources it needs to keep advancing cures.

How Florence turns workflow activity into operational intelligence.

The AI advantage is no longer the AI itself. Every vendor can access models. Very few participate in the workflows where clinical research actually happens. The difference between those who unlock growth with AI vs. those who just use it to improve basic functionality is where AI gets applied, how it integrates with the work, and whether operators can trust what it surfaces.

Embedded, not parallel.

Florence AI runs inside the platforms sites and sponsors already use. No new system to learn. No new password to remember. AI runs where the work already happens.

Operational, not abstract.

Florence applies AI to the workflow activity already flowing through the platform every day: site activity, document movement, approvals, coordination, and sponsor handoffs. Operational intelligence emerges from the work itself, not from disconnected datasets or after-the-fact reporting.

Human review stays central.

Florence keeps humans in the loop on every decision that matters. We assist judgment, we don’t replace it. Every output is reviewed and approved before it moves the trial forward.

Explainable, not black-box.

Operators need to understand what Florence surfaced and why. We prioritize workflow-aligned, explainable intelligence over opaque automation.