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The vision AI blueprint

Tobias Schaffrath Rosario

A walkthrough on how to deliver successful vision AI projects

We have helped hundreds of teams with their vision AI projects — established research institutions like Stanford, global corporations like Bayer, and even one or two FAANG companies.

We have taken what we have learned working with those organizations and created a 20-page guide on the best practices in AI development.

What you will learn

An applied ML approach that works

You don't win in machine learning by having the best code but the best process. Innovative teams like Bayer and Stanford know this. Learn what they, and hundreds of other successful organizations, do.

Data-centric ML

Previously, the focus in vision AI has been on creating better and better models. With the rise of applied and data-centric ML, that is about to change. Learn what matters when getting AI to production.

Concrete walkthrough

Tired of vague promises and chest-thumping marketing blah? We've tried our hardest to concretize how you can be successful based on our experiences, giving you a concrete step-by-step guide to success.

Organization ramp-up template

Interested in starting with vision AI but not sure where to start? We give you all the tips - covering everything from whom to hire to how to deliver your first project.

Download the document here: hasty-vision-ai-blueprint-v5.pdf


Hasty has taken our data labeling to the edge. Both semantic and bounding box labeling has gone from weeks or months on our large data sets to days. For QA, I just reviewed 19,000 labels in 5 hours. WTF!

Removing the risk from vision AI.

Only 13% of vision AI projects make it to production, with Hasty we boost that number to 100%.