Define the work before looking for a supplier
Use this when an AI acquisition or research team needs records from operating companies and must explain what would count as a useful contribution. Start with the intended task rather than a request for a large quantity of data.
Have a task owner, a proposed evaluation process and the main technical or procurement constraints in mind. Describe required evidence without naming private source companies or uploading examples.
Write checks that can produce a decision
Connect each requested record family to the evidence it supplies. If the task concerns resolution quality, specify whether a case needs an outcome, a reason for closure or a link to a later action. A dataset name alone does not define those requirements.
An acceptance criterion identifies what is checked, which evidence supports the check and what happens if it fails. Keep task suitability separate from rights and security review. Passing one does not imply passing the others.
Hand over a requirement that can be revised
The output preserves the task, source requirement, outcome evidence, checks and use boundaries. Its clarification list lets a supplier or evaluator respond to the requirement rather than guess at it.
Use the brief to agree a bounded evaluation and its disclosure permissions. It is not a purchase order or a promise that a matching dataset is available.
An acceptance criterion with a consequence
For a support-resolution evaluation, require each item to retain its request, relevant context and recorded resolution as a connected case. Report missing links separately. Hold a case without a recorded outcome out of the outcome-based test rather than silently treating it as a successful resolution.
Build a sourcing brief
A sourcing brief with task-linked evidence, acceptance checks, failure actions and procurement questions.
Your entries stay on this page. They are not sent or saved. Use high-level descriptions and leave confidential records out.
Use a printable or editable version
Each version contains instructions, a worksheet and a filled example. The example shows how to describe a decision; it makes no claim about an actual company or offer.
Use the result within its limits
The brief does not prove dataset availability, suitability or licensing rights.
Criteria require agreement with the evaluator and responsible procurement, technical and rights reviewers.
Sources behind this method
- NIST AI Risk Management Framework. Voluntary AI risk guidance. It does not certify a dataset or prescribe a licensing contract.