Strategic guidance for health tech teams making disciplined ML investment decisions

When to Talk to Me

You're building health tech and see where ML could help—automating clinical workflows, surfacing insights from unstructured data, predicting patient outcomes—but you're not sure:

• If it makes financial sense (will ROI justify the investment?)
• If you're ready to execute (data quality, team capability, compliance)
• How to avoid expensive mistakes (60-70% of ML projects fail)
• Where to start (too many possibilities, need prioritization)

I help health tech companies answer these questions through two specialized frameworks—and then support implementation when you're ready to build.

Core Frameworks

Pre-ASSESS: ROI Feasibility Framework

Investment: $2,500 | Time: 6-8 hours / 1 day

Answer one critical question before committing development budget: Will this ML project generate positive ROI?

Three questions determine viability:

• Can we quantify business value in dollars?
• Can we estimate true costs (development, infrastructure, maintenance, compliance)?
• Does the math actually work (>3:1 ratio required to proceed)?

You receive: ROI Feasibility presentation and write up with go/no-go recommendation and financial justification for stakeholders.

Best for: Exploring ML opportunities, need executive/board validation, want to avoid $200K-500K mistakes.