A step-by-step guide to transform your professional experience into a structured dataset that AI companies are willing to buy.
dario-avalos
Sagelix
If you’ve made it this far, you probably already understand that your experience has value. The question is: how do you turn it into something you can sell? The answer lies in knowledge datasets.
What Is a Knowledge Dataset?
A knowledge dataset is a structured collection of expert information that can be used to train AI models, create decision support systems, or simply document industry best practices.
Step 1: Identify Your Unique Area of Expertise
Don’t try to cover everything you know. Focus on the area where your knowledge is deepest and most differentiated. What problems have you solved that others can’t?
Step 2: Structure the Information
Unstructured knowledge has little value. You need to organize your expertise into categories, use cases, scenarios, and solutions. Tools like those offered by Sagelix greatly simplify this process.
Step 3: Document Real Cases
Practical cases are pure gold. Every problem you solved, every decision you made, every mistake you avoided can become a valuable data point.
Step 4: Validate and Enrich
A good dataset evolves. Companies like SmartQube have shown that continuous iteration exponentially improves data value.
Step 5: Protect and Monetize
Your knowledge is your intellectual property. Make sure you understand your rights before sharing it. Explore more resources on how to protect your work.
Ready to start? Join Sagelix and receive personalized guidance.
