andremagrini.com

HEALTH AND LIFE SCIENCES

Fractional CRO and AI Governance for Health and Life Sciences

A Fractional CRO in health and life sciences builds the commercial operating system around complex stakeholders, evidence, procurement, implementation, and responsible AI adoption.

WHO IT IS FOR

Which companies are the best fit?

B2B health technology, life-sciences tools, equipment, data, and service companies that need stronger commercial execution without separating revenue decisions from adoption and governance.

EXPECTED RESULT

What should leadership expect?

A revenue system that makes evidence, adoption, governance, and specialist review visible before they become late-stage surprises.

OPERATING PRESSURES

What makes health-market revenue architecture different?

  • The user, economic buyer, procurement team, and risk owner may be different people
  • A technically strong solution lacks a credible evidence package for the buying process
  • Security, privacy, workflow, reimbursement, or implementation questions appear late in deals
  • AI claims move faster than governance, validation, and customer trust

MANDATE

What can Andre lead without replacing specialists?

  • Segment selection, buying-committee mapping, value proposition, and evidence requirements
  • Pipeline stages that expose clinical, technical, procurement, privacy, and implementation dependencies
  • Forecast governance and executive escalation for complex opportunities
  • AI portfolio and human-control decisions connected to commercial adoption

FIRST 90 DAYS

A sector-specific operating sequence

Days 1-30: Diagnose
  • Map stakeholders, workflows, procurement gates, evidence gaps, and stalled opportunities
  • Audit claims, implementation assumptions, forecast criteria, and AI decision ownership
  • Separate commercial constraints from legal, clinical, privacy, and technical questions requiring specialists
Days 31-60: Install
  • Define priority segments and proof required for each buying committee
  • Rebuild opportunity stages around real approval and implementation events
  • Install governance for AI claims, exceptions, human review, and customer evidence
Days 61-90: Operate and transfer
  • Run deal and portfolio reviews with commercial and specialist owners
  • Measure stage movement, approval delays, implementation readiness, and adoption evidence
  • Transfer playbooks, escalation paths, and board reporting to internal leaders

METRICS

Which indicators should move?

  • Qualified-opportunity conversion
  • Time in procurement and approval stages
  • Implementation acceptance
  • Time to customer value
  • Renewal and expansion
  • AI exception and human-review rate

ENGAGEMENT FIT

Who should not hire this service?

Not a fit for organizations seeking medical advice, clinical validation, HIPAA certification, regulatory representation, or legal approval from a revenue executive.

Scope boundary: Andre does not provide medical, clinical, legal, privacy, or regulatory advice. Those decisions remain with licensed counsel, privacy officers, clinical leaders, security teams, and relevant authorities.

OPERATING AUTHORITY

What evidence supports Andre’s approach?

Andre Magrini led the AGI Brazil operation as it scaled from approximately $35M to more than $150M in revenue through commercial organization, channel execution, management cadence, and P&L accountability. This is historical operating context, not a promise of future performance.

Read the documented AGI operating case

FAQ

Questions buyers ask before engaging

Can a Fractional CRO work with compliance and clinical teams?

Yes. The role is to bring their requirements into segmentation, claims, opportunity stages, forecast evidence, implementation planning, and executive decisions without replacing their authority.

Does this service make a company HIPAA compliant?

No. HIPAA applicability and compliance require qualified legal, privacy, security, and operational review. The commercial system can make those dependencies visible and governed.

How should AI claims be handled in health sales?

Claims should be bounded by intended use, evidence, data context, known limitations, human controls, and accountable review before they enter customer-facing materials or workflows.

Diagnose the operating constraint before choosing the solution.

Start with the revenue fingerprint, evidence, and decision rights.

Request an AI Revenue Diagnostic