Risk & Readiness Assessment

Is your vision AI ready for the real world?

Many vision AI projects struggle long before full deployment — but often the warning signs show early. Variability in data, mismatched models, or overfitting to lab conditions can all erode performance, trust, and value under real-world constraints.

Whether you’re launching a new initiative or cleaning up a partially built system, unaddressed risks tend to compound, making recovery harder and more expensive.

Typical pitfalls include:

• Incomplete or biased imagery — missing conditions, devices, or geographies.

• Annotation bottlenecks — underestimated cost, scale, or labeling consistency.

• Misaligned model choices — architectures too large for edge devices or too weak for variability.

• Weak validation plans — failures surface only when tested in new sites, on new devices, or under new conditions.

• Missing domain expertise — models optimized for benchmarks rather than solving the real-world problem that matters

By the time these issues appear, months of effort and budget have already been lost — and the project is heading straight for a breakdown.

The Fix: Stress-Test Your Assumptions Build

This is a short, focused engagement rooted in deep domain experience and designed for maximum clarity and impact.

With the Risk & Readiness Assessment, together we:

• Surface risks hidden in your data, modeling assumptions, validation process, and domain alignment

• Evaluate how the project aligns with real use cases — not just lab benchmarks

• Prioritize the most critical issues blocking robustness and scalability

• Define practical, actionable next steps for the next 30–90 days

• Align all stakeholders — technical leads, domain experts, and decision-makers — on a shared plan

This engagement isn’t about building— it’s about diagnosing, aligning, and de-risking.

Who It’s For

This assessment is ideal when:

• You’re starting a new vision AI project and want confidence from the outset

• You have an existing or partially built model and suspect it may not survive real-world conditions

• You need to recover a stalled project or re-align direction

• Organizations with large image datasets but unclear annotation or pretraining strategy.

• Startups and scale-ups needing to de-risk ambitious projects before investors or leadership sign off.

• R&D groups seeking confidence that vision models will hold up beyond the lab and solve problems that matter in the field.

What You Get

• Structured Questionnaire: A short set of questions to capture your project goals, data sources, annotation strategy, modeling plans, and constraints. This must be completed at least 48 hours before the working session so I can review it in advance.

• Expert Review: I analyze your responses to surface potential risks and blind spots.

• 90-Minute Live Session: A focused discussion to dig into the highest-priority risks and clarify where your project may run into challenges and discuss mitigation.

• Concise Report: A 5–7 page summary highlighting the top risks, recommended mitigation plan, and practical next steps.

Why It Matters

A few hours of diagnosis now can prevent months of rework, wasted data collection, or trust erosion later:

• Avoid unnecessary training cycles, rewrites, or architecture rewrites

• Reduce unnecessary data collection and annotation expense

• Protect stakeholder confidence — executives, investors, or domain leaders

• Ensure your models have a shot of making it beyond prototype into real, sustained use

Even without a follow-on engagement, you’ll gain strategic clarity — a clear, defensible path to strengthen your model and de-risk your next phase.

If you’d like help implementing the recommendations, we can discuss a follow-on advisory partnership — but there’s no obligation.

Investment

The assessment 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

A single misstep in scoping, data, or modeling can cost far more than this assessment. Investing a few hours now helps you avoid months of rework and credibility loss later.

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?