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.
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.
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.
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.
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
80% of vision AI teams don’t make it to production because of bad or insufficient data. Hasty solves removes that risk.
