xAGI LABS / DATA PROGRAMS
AI dataset readiness checklist
Identify the information missing from a responsible sourcing or licensing conversation.
Inventory the evidence, not just the files
Keep a source register describing collection dates, owners, contributors, licenses, versions and known exclusions. Separate what you know from assumptions that still require confirmation. Check whether the proposed model use differs from the purpose originally communicated to contributors. Do not treat completion of a checklist as a legal conclusion.
Review usefulness and coverage
Describe the population, languages, environments and time period represented. Note missing groups, duplicates, label quality and any preprocessing. Decide what a representative review sample should contain and which acceptance checks can be repeated. Document limitations so a buyer can evaluate fit before discussing scale.
Keep the first exchange small
Share a high-level description first. Agree a secure review and transfer process before sending sample records or source code. A later review may need to resolve third-party rights, confidentiality, personal information and usage restrictions. The checklist below helps organize that discussion; it does not certify a dataset or produce a price.
Prepare for a licensing conversation
This checklist identifies missing information. It does not value a dataset, verify rights or authorize its use.
Start with a useful conversation.
Tell us the model task or source you want to explore. We establish feasibility, quality and rights before discussing delivery.
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