From business records to agent evaluation environments
A dataset is not automatically a runnable environment. Agent evaluation needs a defined task, allowed actions and a way to judge outcomes.
Read the guide ↗Distinctive observations and specialist workflows may support a dataset license, recurring delivery or a deeper research partnership. Start with the evidence and intended use.
What is difficult to observe elsewhere? What decisions or outcomes can your records explain? What remains unproven?
A versioned package of authorized examples, documented fields and known limitations.
Fresh data delivered on an agreed cadence when new evidence serves a continuing need.
Worked examples, corrections and criteria that make specialized performance testable.
A scoped project around state, actions and outcomes, with additional technical requirements.
A dataset is not automatically a runnable environment. Agent evaluation needs a defined task, allowed actions and a way to judge outcomes.
Read the guide ↗Distinctiveness often comes from context: a rare decision, a difficult exception or a reliably measured result. It does not require an unusual software platform.
Read the guide ↗A bounded dataset gives both parties something concrete to evaluate. Define its contents, intended use and known limitations before discussing scale.
Read the guide ↗Recurring access makes sense when new data improves a continuing use case. Repeated delivery of the same archive does not create fresh value.
Read the guide ↗Useful expert material can include worked examples, corrections and clear outcome criteria. A procedure document alone may leave important judgments unstated.
Read the guide ↗Some research uses observations of how a system changes after an action. Ordinary activity logs may capture only part of that relationship.
Read the guide ↗Explore an automated estimate report. No records or exports needed.