New: Maxis AI Workforce now live across clinical operations.Learn more →

Maxis AI — THE FIRST AI WORKFORCE IN CLINICAL TRIALS
Case Studies Gated Case Study

Case Study

SMB CRO: 2–3× Growth, $200–400K Saved

Winning enterprise bids without scaling only through hiring.

Case StudyFebruary 2026SMB CRO
SMB CRO: 2–3× Growth, $200–400K Saved

About this case study

What's inside

Winning enterprise bids without scaling only through hiring. This case study unpacks the operating model, governance choices, and measured outcomes behind a real customer deployment — written for teams evaluating similar engagements.

Key takeaways

What you'll learn

  • The customer's pre-deployment baseline and target outcomes.
  • How governance was structured before scaling the agentic workflow.
  • Measured improvements in cycle time, cost recovery, and quality KPIs.
  • Lessons learned, including what would be done differently in hindsight.
  • A replicable blueprint for similar sponsor, CRO, or site-network teams.
James O'Connell

About the author

James O'Connell

VP, R&D Economics

James writes about the financial mechanics of clinical trials and where AI moves the needle on per-study burn rate and submission timelines.

Looking for AI Workforce for clinical trials?

Explore our AI Workforce Platform

See how AI agents are transforming study startup, data management, oversight, and regulatory submissions.