A useful retrieval collection connects realistic questions to the right version of the right evidence, including questions the available corpus cannot answer.
Define the knowledge boundary
Identify the policies, procedures, product documents, reports, or correspondence the system should search. Record document versions and effective dates where relevant. Specify a hypothetical user’s access and the decision time so a correct answer does not rely on restricted or future material.
Write task-based questions
Use questions tied to a business workflow, such as locating an approval exception or finding a product compatibility rule. Preserve the context needed to interpret them. Include short lookups, multi-document questions, ambiguous requests, and no-answer examples rather than asking only questions copied from document headings.
Specify answer evidence
Require stable source identifiers and supporting passages for expected answers. Distinguish topical matches from passages that actually justify a conclusion. For conflicting versions, state the controlling rule or expected uncertainty behavior. Review a sample of evidence links manually before relying on aggregate retrieval scores.
Discuss source fit with Fiund
Share the corpus boundary, question format, evidence schema, and review requirements. Each proposed source needs its own project assessment, including sensitive information and permitted scope. The initial aim is a well-documented pilot that exposes retrieval gaps and supports a concrete decision about further sourcing.
Include in your inquiry
- Corpus and version boundary
- Question examples and no-answer policy
- Passage-level evidence schema
- Access, handling, and source-review scope