Last-Mile AI Gap Diagnostic

Why Most Vision AI Fails

Over 80% of AI projects collapse when they move from validation to the real world. Models that perform beautifully in the lab often stumble when faced with real-world complexity.

The causes are predictable:

• Technical fragility — accuracy drops when conditions shift (new sites, scanners, sensors, or populations).

• Unreliable modeling — brittle predictions, overfitting, or shortcuts that don’t generalize.

• Lack of trust — biased or opaque predictions erode confidence with stakeholders.

• Stalled adoption — models that can’t scale or drive real decisions get stuck in pilot purgatory.

This is the last-mile AI gap — the costly disconnect between promising research and real-world results.

The Solution: A Focused Diagnostic

The Last-Mile AI Gap Diagnostic is a structured, high-value engagement designed to uncover hidden risks before they derail your project.

In a 90-minute working session plus a written summary, I’ll:

• Review your data, modeling, and domain approach

• Pinpoint vulnerabilities across three dimensions:
  • Technical foundations — accuracy, reliability, robustness
  • Trust — fairness, explainability, accountability
  • Adoption — actionability, scalability, sustainability

• Identify where your project is most likely to fail in the real world

• Prioritize high-leverage actions to strengthen robustness and credibility

• Frame next steps in language that resonates with executives, investors, and regulators

Note: Once you book, you’ll receive a short questionnaire to capture context on your project. This must be completed at least 48 hours before the session so I can review it in advance.

What You’ll Walk Away With

By the end, you’ll have:

• A clear map of risks across technical, trust, and adoption dimensions

• A prioritized roadmap to make your model ready for the real world

• Executive-ready framing to build confidence with stakeholders

• Confidence that your team is focused on what drives real-world results — not just novelty

Who It’s For

The diagnostic is designed for science-driven teams who can’t afford costly failures:

• Startups preparing for pilots, fundraising, or regulatory milestones

• Pharma & biotech teams validating biomarkers or trial endpoints

• Earth observation & geoscience organizations scaling prototypes to production

• Any team building vision AI that must survive the real world

Investment

The diagnostic is a fixed-fee engagement with pricing tailored to your organization’s stage:

• Startups: $3,000 flat fee — scoped for lean teams with fewer stakeholders

• Larger organizations: typically $5,000–$7,500, depending on scope and number of stakeholders

The cost of one failed sprint, dataset, or trial can exceed this many times over. This diagnostic helps you avoid becoming part of the 80%.

Don’t just take my word for it…

Heather has accelerated the development of our machine learning projects by challenging the status quo and introducing the team to new approaches. She helped us get out of the echo chamber and brought an outside perspective with very relevant alternative approaches that would have taken a lot longer to do on our own.

-- Joe Sturonas, Ancera, VP of Systems Development

Pixel Scientia provides valuable insights for Gestalt's image analysis product development. Heather has deep understanding of digital pathology and machine learning and their application to whole slide images. Her in-depth review of the current state of the art research has enabled Gestalt to rapidly focus our machine learning efforts on approaches that are yielding value for our pathologists and their patients.

-- Brian Napora, Gestalt Diagnostics, VP of Sales & Product Management

Still have questions?